Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification | Paper Citation Record

Observation be51c658-c095-4322-ab77-4ae19d16f998 · outbound

This paper cites Spatio-temporal repre- sentation factorization for video-based person re-identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Spatio-temporal repre- sentation factorization for video-based person re-identification

Reference 1

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Observation 5331d4ee-28fd-4796-873e-5450b91e498e · outbound

This paper cites Salient-to-broad transition for video person re-identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Salient-to-broad transition for video person re-identification

Reference 2

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Observation 56d5aa24-dbd6-4916-9944-84dbd68fdb78 · outbound

This paper cites Event-guided person re- identification via sparse-dense complementary learning.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Event-guided person re- identification via sparse-dense complementary learning

Reference 3

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This paper cites End-to-end object detection with transformers.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification End-to-end object detection with transformers

Reference 4

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Observation ecdd2d22-8b68-49ec-a390-b9c5ee31bea8 · outbound

This paper cites Video person re-identification with competitive snippet- similarity aggregation and co-attentive snippet embedding.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Video person re-identification with competitive snippet- similarity aggregation and co-attentive snippet embedding

Reference 5

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This paper cites an unresolved cited work.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Unresolved cited work

Reference 6

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Observation 433ae3d1-7382-441d-aca6-116b6032def2 · outbound

This paper cites Diffrate: Differentiable compression rate for efficient vision transformers.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Diffrate: Differentiable compression rate for efficient vision transformers

Reference 7

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Observation 00f87cd1-c2b5-4f55-b84a-5f9968001dca · outbound

This paper cites Reality3dsketch: Rapid 3d modeling of objects from single freehand sketches.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Reality3dsketch: Rapid 3d modeling of objects from single freehand sketches

Reference 8

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Observation 90c2b3f2-02d5-4622-905b-d27dad233155 · outbound

This paper cites Abd-net: Attentive but diverse person re-identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Abd-net: Attentive but diverse person re-identification

Reference 9

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Observation e96a7da9-8e65-4853-bd8f-95f28a4ac6fb · outbound

This paper cites Deep3DSketch: 3D modeling from Free-hand Sketches with View- and Structural-Aware Adversarial Training.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Deep3DSketch: 3D modeling from Free-hand Sketches with View- and Structural-Aware Adversarial Training

Reference 10

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This paper cites SAM2-Adapter: Evaluating & Adapting Segment Anything 2 in Downstream Tasks: Camouflage, Shadow, Medical Image Segmentation, and More.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification SAM2-Adapter: Evaluating & Adapting Segment Anything 2 in Downstream Tasks: Camouflage, Shadow, Medical Image Segmentation, and More

Reference 11

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Observation 1c5017d8-2451-4f00-bb52-7ab188e989c6 · outbound

This paper cites Reasoning3D -- Grounding and Reasoning in 3D: Fine-Grained Zero-Shot Open-Vocabulary 3D Reasoning Part Segmentation via Large Vision-Language Models.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Reasoning3D -- Grounding and Reasoning in 3D: Fine-Grained Zero-Shot Open-Vocabulary 3D Reasoning Part Segmentation via Large Vision-Language Models

Reference 12

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Observation eef637cf-3f38-4267-ae1b-5f4386982dc5 · outbound

This paper cites Sam-adapter: Adapting segment anything in underperformed scenes.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Sam-adapter: Adapting segment anything in underperformed scenes

Reference 13

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Observation ebd7810f-a237-4ada-9c16-2cfd45f69fbf · outbound

This paper cites Masked-attention mask transformer for universal image segmentation.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Masked-attention mask transformer for universal image segmentation

Reference 14

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Observation 3c1a51ba-db07-409b-9872-9cac7dab837b · outbound

This paper cites Towards accurate post-training quantization for vision transformer.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Towards accurate post-training quantization for vision transformer

Reference 15

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Observation 0f9310be-8449-4ff2-ab3d-872ad65edcf0 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 16

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Observation f6aab266-ce41-40d9-85be-40e8511a2972 · outbound

This paper cites Eventful transformers: Leveraging temporal redundancy in vision transformers.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Eventful transformers: Leveraging temporal redundancy in vision transformers

Reference 17

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Observation 54c3c877-9305-460e-8706-b375752924b5 · outbound

This paper cites Video- based person re-identification with spatial and temporal memory net- works.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Video- based person re-identification with spatial and temporal memory net- works

Reference 18

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Observation 656a2bd3-e1a5-49af-a9fc-74650e0963de · outbound

This paper cites Motion adaptive pose estimation from compressed videos.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Motion adaptive pose estimation from compressed videos

Reference 19

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Observation 0480bfbf-e940-47fd-9373-93d6ac9a172c · outbound

This paper cites Sta: Spatial-temporal attention for large-scale video-based person re- identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Sta: Spatial-temporal attention for large-scale video-based person re- identification

Reference 20

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Observation f5749dd6-6132-4cd6-9556-a1ecc125c45d · outbound

This paper cites SparseFormer: Sparse Visual Recognition via Limited Latent Tokens.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification SparseFormer: Sparse Visual Recognition via Limited Latent Tokens

Reference 21

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Observation 3f4a3073-e7f5-4911-b942-92c7be60e771 · outbound

This paper cites Appearance-preserving 3d convolution for video-based person re-identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Appearance-preserving 3d convolution for video-based person re-identification

Reference 22

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Observation d4c22ab1-99fb-4af4-b6f4-033f63cdd966 · outbound

This paper cites Flatten transformer: Vision transformer using focused linear attention.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Flatten transformer: Vision transformer using focused linear attention

Reference 23

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Observation acb84bea-0f12-432f-985d-9a08d8dfd446 · outbound

This paper cites Deep residual learning for image recognition.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Deep residual learning for image recognition

Reference 24

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Observation 4d63f547-094d-41fa-b1c5-28796c2e2061 · outbound

This paper cites Transreid: Transformer-based object re-identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Transreid: Transformer-based object re-identification

Reference 25

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Observation c1442edd-9dfb-4961-9f3d-beb9a487176d · outbound

This paper cites Bicnet-tks: Learning efficient spatial-temporal representation for video person re-identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Bicnet-tks: Learning efficient spatial-temporal representation for video person re-identification

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T10:34:00.679988Z

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Observation 46249f9c-6e96-4396-a7bc-f6ea6c22c8d4 · outbound

This paper cites Temporal complementary learning for video person re-identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Temporal complementary learning for video person re-identification

Reference 27

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Observation 72827808-4fda-42c7-86af-a46a71c96b7a · outbound

This paper cites Vrstc: Occlusion-free video person re-identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Vrstc: Occlusion-free video person re-identification

Reference 28

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Observation 9bc71934-e46b-4d09-a639-34b90dd9c969 · outbound

This paper cites Orthogonal transformer: An efficient vision transformer backbone with token orthogonalization.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Orthogonal transformer: An efficient vision transformer backbone with token orthogonalization

Reference 29

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Observation 1517c3fa-2eb8-4df8-88d9-3fbec8c5e1a6 · outbound

This paper cites Reasoning and tuning: Graph attention network for occluded person re- identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Reasoning and tuning: Graph attention network for occluded person re- identification

Reference 30

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This paper cites En- hancing person re-identification performance through in vivo learning.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification En- hancing person re-identification performance through in vivo learning

Reference 31

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This paper cites Discrete Latent Perspective Learning for Segmentation and Detection.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Discrete Latent Perspective Learning for Segmentation and Detection

Reference 32

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This paper cites Fast decoding in sequence models using discrete latent variables.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Fast decoding in sequence models using discrete latent variables

Reference 33

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This paper cites Spvit: Enabling faster vision transformers via latency-aware soft token pruning.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Spvit: Enabling faster vision transformers via latency-aware soft token pruning

Reference 34

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Observation 2bd61ef7-1de5-4404-b5a0-54fe6bd6d05b · outbound

This paper cites Global-local temporal representations for video person re-identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Global-local temporal representations for video person re-identification

Reference 35

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Observation 6afe1780-49fc-4568-ba2c-0b287a391b1b · outbound

This paper cites Multi-scale 3d convolu- tion network for video based person re-identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Multi-scale 3d convolu- tion network for video based person re-identification

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:04.419340Z

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This paper cites Diverse part discovery: Occluded person re-identification with part-aware transformer.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Diverse part discovery: Occluded person re-identification with part-aware transformer

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:04.374263Z

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Observation 8d2f5ad6-4692-4481-94fe-254745f1180a · outbound

This paper cites Svitt: Tem- poral learning of sparse video-text transformers.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Svitt: Tem- poral learning of sparse video-text transformers

Reference 38

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Observation 58878bff-9f9c-4afe-a621-d8b63b922a9b · outbound

This paper cites Efficientformer: Vision transformers at mobilenet speed.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Efficientformer: Vision transformers at mobilenet speed

Reference 39

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This paper cites Evit: Expediting vision transformers via token reor- ganizations.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Evit: Expediting vision transformers via token reor- ganizations

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:04.274361Z

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Observation 3c36b440-baa5-418a-a0da-b9b18c4916ea · outbound

This paper cites Not all patches are what you need: Expediting vision transformers via token reorganizations.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Not all patches are what you need: Expediting vision transformers via token reorganizations

Reference 41

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Observation cde5d3dd-fed4-471b-87f7-cccb5775bfdd · outbound

This paper cites Supervised masked knowledge distillation for few-shot transformers.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Supervised masked knowledge distillation for few-shot transformers

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:04.208933Z

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Observation d0bd5b39-b890-4dba-9249-d399d71bbefd · outbound

This paper cites A versatile model for packet loss visibility and its application to packet prioritization.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification A versatile model for packet loss visibility and its application to packet prioritization

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:04.177601Z

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Observation 9f6afe2c-12cc-44d1-a3c9-2ed433e9d0a5 · outbound

This paper cites Learning modal-invariant and temporal-memory for video-based visible-infrared person re- identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Learning modal-invariant and temporal-memory for video-based visible-infrared person re- identification

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:04.122754Z

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Observation 4f6bf0da-4e50-448a-a1de-2e66d2fb3113 · outbound

This paper cites Video-based person re-identification with accumulative motion context.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Video-based person re-identification with accumulative motion context

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:04.088878Z

Source-reported events for the cited work

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Observation f4d99539-83c9-4f2b-8c1f-82c38fbe9e05 · outbound

This paper cites Spatial-temporal correlation and topology learning for person re- identification in videos.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Spatial-temporal correlation and topology learning for person re- identification in videos

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:04.034501Z

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Observation c6fa7295-253d-468f-a89e-dd9337dd5827 · outbound

This paper cites Fre- quency information disentanglement network for video-based person re-identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Fre- quency information disentanglement network for video-based person re-identification

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:03.999890Z

Source-reported events for the cited work

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Observation 54402849-bfa5-4d3f-952c-485f8bc285b6 · outbound

This paper cites Deeply coupled convolution–transformer with spatial–temporal complementary learning for video-based person re-identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Deeply coupled convolution–transformer with spatial–temporal complementary learning for video-based person re-identification

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:03.974301Z

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Observation abdb1110-f433-42b1-b98b-5c1a6d9e8df6 · outbound

This paper cites Watching you: Global-guided reciprocal learning for video-based person re-identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Watching you: Global-guided reciprocal learning for video-based person re-identification

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:03.940849Z

Source-reported events for the cited work

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Observation 7b1846f5-bab4-4e15-91f6-5f4efc4a705c · outbound

This paper cites Noisyquant: Noisy bias-enhanced post-training activation quantization for vision transformers.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Noisyquant: Noisy bias-enhanced post-training activation quantization for vision transformers

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:03.899867Z

Source-reported events for the cited work

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Observation 1d5f7440-c864-4760-9294-77c39c6b51a7 · outbound

This paper cites Post-training quantization for vision transformer.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Post-training quantization for vision transformer

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:03.870990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ffc1e182-1a4c-48d5-a5ad-84c3e9cf45cc · outbound

This paper cites Label-guided attention distillation for lane segmentation.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Label-guided attention distillation for lane segmentation

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:03.833979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 008f223d-c2e5-40c2-b586-8e9b171ae2b3 · outbound

This paper cites Learning based multi-modality image and video compression.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Learning based multi-modality image and video compression

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:03.809597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation df999c87-0a0f-47b2-af23-0d45ca647b49 · outbound

This paper cites Ppt: token- pruned pose transformer for monocular and multi-view human pose estimation.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Ppt: token- pruned pose transformer for monocular and multi-view human pose estimation

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:03.782259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 9772c7e4-0af2-4a67-916a-7fee1d309a52 · outbound

This paper cites Re- current convolutional network for video-based person re-identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Re- current convolutional network for video-based person re-identification

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:03.759689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 1d7d963a-c84f-4d36-a925-bf5f54620d50 · outbound

This paper cites Deep spectral methods: A surprisingly strong baseline for unsupervised semantic segmentation and localization.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Deep spectral methods: A surprisingly strong baseline for unsupervised semantic segmentation and localization

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:03.714484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 02aaef4e-ed0d-4ca7-9789-230b272472b6 · outbound

This paper cites Adavit: Adaptive vision transformers for efficient image recognition.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Adavit: Adaptive vision transformers for efficient image recognition

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:03.670264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 047631c8-c271-44d9-913c-f170ded2615e · outbound

This paper cites Counterfac- tual attention learning for fine-grained visual categorization and re- identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Counterfac- tual attention learning for fine-grained visual categorization and re- identification

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:03.641634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4aa80c06-eaaf-4974-81f7-cd986963a15e · outbound

This paper cites Dynamicvit: Efficient vision transformers with dynamic token sparsification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Dynamicvit: Efficient vision transformers with dynamic token sparsification

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:03.601500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4b95de68-333b-43fd-a312-13f738dbcf05 · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification SAM 2: Segment Anything in Images and Videos

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-10T10:34:01.004449Z

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Observation 2e020797-d634-47ca-aded-044083e250ea · outbound

This paper cites Co- segmentation inspired attention networks for video-based person re- identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Co- segmentation inspired attention networks for video-based person re- identification

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:03.553221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 94818aaa-7c94-457d-bed4-b8360c2c15e8 · outbound

This paper cites Patch slimming for efficient vision transformers.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Patch slimming for efficient vision transformers

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:03.522141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ebb60d0e-9153-4c83-b7f6-e9a0d53dc7c0 · outbound

This paper cites Multi-stage spatio-temporal aggregation transformer for video person re-identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Multi-stage spatio-temporal aggregation transformer for video person re-identification

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:03.481702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 921d8ada-28a8-41f3-a01e-09366a84df14 · outbound

This paper cites Training data-efficient image transformers & distillation through attention.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Training data-efficient image transformers & distillation through attention

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:03.446338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4f2d0bb4-95a6-41d1-9d37-f8429ae60f87 · outbound

This paper cites Efficient video transformers with spatial-temporal token selection.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Efficient video transformers with spatial-temporal token selection

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:03.405956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a7e11d25-784c-45bc-90d0-8ae283a164d5 · outbound

This paper cites Pyramid spatial-temporal aggregation for video-based person re-identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Pyramid spatial-temporal aggregation for video-based person re-identification

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:03.369877Z

Source-reported events for the cited work

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Observation 307c01be-5d1a-4f31-aeca-b5319d7704a0 · outbound

This paper cites Joint token pruning and squeezing towards more aggressive compression of vision transformers.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Joint token pruning and squeezing towards more aggressive compression of vision transformers

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:03.332193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0aa13f07-9948-4b24-873c-767070e4e605 · outbound

This paper cites Overview of the h.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Overview of the h

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:03.299580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 12292abd-d6f3-456e-a744-a2af9f2b9a37 · outbound

This paper cites Cavit: Contextual alignment vision transformer for video object re-identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Cavit: Contextual alignment vision transformer for video object re-identification

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:03.261838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation cf4bce51-30f0-43f1-af45-aab88f3b625f · outbound

This paper cites Tinyvit: Fast pretraining distillation for small vision transformers.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Tinyvit: Fast pretraining distillation for small vision transformers

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:03.236096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 8a4f1536-7211-4faa-b76d-70eb0606caf7 · outbound

This paper cites Learning resolution- adaptive representations for cross-resolution person re-identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Learning resolution- adaptive representations for cross-resolution person re-identification

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:03.186474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 3db7aa8e-8600-4560-85b4-a18c9a2ae359 · outbound

This paper cites Temporal complementarity-guided reinforcement learning for image- to-video person re-identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Temporal complementarity-guided reinforcement learning for image- to-video person re-identification

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:03.140192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 31e0a4cd-b324-453f-81e6-ab3037f547d7 · outbound

This paper cites Adaptive graph representation learning for video person re- identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Adaptive graph representation learning for video person re- identification

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:03.110319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 894f8484-1cd6-4cb9-bf6c-b0f81ca7ca5f · outbound

This paper cites Segformer: Simple and efficient design for semantic segmentation with transformers.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Segformer: Simple and efficient design for semantic segmentation with transformers

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:03.084236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e897bd96-5ac3-438c-9781-cdc94afa0989 · outbound

This paper cites Learning multi-granular hypergraphs for video-based person re- identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Learning multi-granular hypergraphs for video-based person re- identification

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:03.049824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation aa82aabd-5183-453a-ac1d-84549556343e · outbound

This paper cites Spatial-temporal graph convolutional network for video-based person re-identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Spatial-temporal graph convolutional network for video-based person re-identification

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:03.023721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d1300d57-c14c-4878-b45b-e29a0df9bdcb · outbound

This paper cites Stfe: A comprehensive video-based person re-identification network based on spatio-temporal feature enhancement.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Stfe: A comprehensive video-based person re-identification network based on spatio-temporal feature enhancement

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:02.990324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a8e9a7b2-4c4b-41b0-9b1c-cd466559acd9 · outbound

This paper cites Shiftaddvit: Mixture of multiplication primitives towards efficient vision trans- former.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Shiftaddvit: Mixture of multiplication primitives towards efficient vision trans- former

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:02.950869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d64b79cf-b33f-4b05-9b3b-d6d84fbf11f1 · outbound

This paper cites an unresolved cited work.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Unresolved cited work

Reference 79

Resolution: unresolved; raw_fallback, observed 2026-08-10T10:34:02.912112Z

Source-reported events for the cited work

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Observation 18378f3d-7930-4126-9b1c-acfc7e872773 · outbound

This paper cites Tf-clip: Learning text-free clip for video-based person re-identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Tf-clip: Learning text-free clip for video-based person re-identification

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:02.868769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 98e448b3-cf8c-443d-9d51-808a34e17e79 · outbound

This paper cites Metaformer is actually what you need for vision.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Metaformer is actually what you need for vision

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:02.829017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d9437572-3996-44cf-9677-5dc8e707cb0d · outbound

This paper cites Ptq4vit: Post-training quantization for vision transformers with twin uniform quantization.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Ptq4vit: Post-training quantization for vision transformers with twin uniform quantization

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:02.805325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 903b4ee1-7d31-409a-85e6-e0761d354f86 · outbound

This paper cites Resmatch: Referring expression segmentation in a semi-supervised manner.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Resmatch: Referring expression segmentation in a semi-supervised manner

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:02.766980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c6465497-0326-48a4-9472-6a3c67ae4bd7 · outbound

This paper cites Minivit: Compressing vision transformers with weight multiplexing.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Minivit: Compressing vision transformers with weight multiplexing

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:02.721102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation cf8422f9-5cbc-401c-8289-d1aae970818c · outbound

This paper cites Magic tokens: Select diverse tokens for multi-modal object re-identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Magic tokens: Select diverse tokens for multi-modal object re-identification

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:02.494523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 06b90b88-2f2d-4c88-a479-36a41fc82c4d · outbound

This paper cites Learning bidirectional temporal cues for video-based person re-identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Learning bidirectional temporal cues for video-based person re-identification

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:02.469527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 8bbb94ba-6850-468c-9bb4-4e9b1cef9310 · outbound

This paper cites Multi- granularity reference-aided attentive feature aggregation for video- based person re-identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Multi- granularity reference-aided attentive feature aggregation for video- based person re-identification

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:02.444522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0c313ad0-a03e-4e60-b764-b4dc5a424a5b · outbound

This paper cites Structure- aware cross-modal transformer for depth completion.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Structure- aware cross-modal transformer for depth completion

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:02.413916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 9b79195b-35f0-48b5-bf5f-b905e06fcb14 · outbound

This paper cites Attribute-driven feature disentangling and temporal aggregation for video person re-identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Attribute-driven feature disentangling and temporal aggregation for video person re-identification

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:02.385764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d2aa7ecb-ecf0-4824-a9b9-ebbd4bf1d86f · outbound

This paper cites 3d human pose estimation with spatial and temporal transformers.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification 3d human pose estimation with spatial and temporal transformers

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:02.351170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 48e554cd-45a1-4044-9b37-dad578f6e048 · outbound

This paper cites Person Re-identification: Past, Present and Future.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Person Re-identification: Past, Present and Future

Reference 91

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Observation 95d447e4-cb39-44ef-afde-87efb668f158 · outbound

This paper cites Joint discriminative and generative learning for person re-identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Joint discriminative and generative learning for person re-identification

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:02.316212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation eda5782f-e048-46b1-94a8-a659335c6634 · outbound

This paper cites Omni-scale feature learning for person re-identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Omni-scale feature learning for person re-identification

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:02.274860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c593dd8b-0ae2-4291-a6e3-eb601c39fd4b · outbound

This paper cites See the forest for the trees: Joint spatial and temporal recurrent neural networks for video-based person re-identification.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification See the forest for the trees: Joint spatial and temporal recurrent neural networks for video-based person re-identification

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:02.248839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 97d4ea06-622f-4d46-99b0-c209172392c3 · outbound

This paper cites Llafs: When large language models meet few-shot segmentation.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Llafs: When large language models meet few-shot segmentation

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:02.207072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 84fc00dd-55fa-4b52-9401-0faccc751e8b · outbound

This paper cites Continual semantic segmentation with automatic memory sample selection.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Continual semantic segmentation with automatic memory sample selection

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:02.175854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 9f95fbcf-1407-4e71-bec4-57dbd7de63f7 · outbound

This paper cites Learning gabor texture features for fine-grained recognition.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Learning gabor texture features for fine-grained recognition

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:02.146109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation cc7719c1-30c2-4586-8b78-e6b0371cee33 · outbound

This paper cites Addressing background context bias in few-shot segmentation through iterative modulation.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Addressing background context bias in few-shot segmentation through iterative modulation

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:34:02.117096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 25b2325f-84a0-44fc-a614-f97f6590f3d8 · outbound

This paper cites IBD: Alleviating Hallucinations in Large Vision-Language Models via Image-Biased Decoding.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification IBD: Alleviating Hallucinations in Large Vision-Language Models via Image-Biased Decoding

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This paper cites Learning statistical texture for semantic segmentation.

Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification Learning statistical texture for semantic segmentation

Reference 100

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