Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval | Paper Citation Record

Observation e4aac53a-8eba-4245-841e-e1b4050517d1 · outbound

This paper cites GPT-4 Technical Report.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval GPT-4 Technical Report

Reference 1

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Observation b8ea0d4c-9b69-4cf2-862a-5c3cb8f73ddb · outbound

This paper cites Learning representations and generative models for 3d point clouds.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Learning representations and generative models for 3d point clouds

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:14.859434Z

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Observation 999751b7-9af4-4ca8-a8cc-b92716dae7db · outbound

This paper cites Flamingo: a visual language model for few-shot learning.NeurIPS, 35: 23716–23736, 2022.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Flamingo: a visual language model for few-shot learning.NeurIPS, 35: 23716–23736, 2022

Reference 3

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Observation a43544f7-af1f-4cbc-8234-efa0de1b77c9 · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 4

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Observation 4fcf1764-3975-4614-a34d-31129cb75b39 · outbound

This paper cites Qwen2.5-VL Technical Report.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Qwen2.5-VL Technical Report

Reference 5

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Observation ee5ee636-8bd2-4873-aacc-a58928464e15 · outbound

This paper cites Shape matching and object recognition using shape contexts.IEEE TPAMI, 24(4):509–522, 2002.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Shape matching and object recognition using shape contexts.IEEE TPAMI, 24(4):509–522, 2002

Reference 6

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Observation 58286fd9-015a-4f4e-984a-91c3fb966a67 · outbound

This paper cites On visual similarity based 3d model retrieval.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval On visual similarity based 3d model retrieval

Reference 7

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Observation 5c7843a9-6416-421f-b833-a417b1c5031d · outbound

This paper cites Shikra: Unleashing Multimodal LLM's Referential Dialogue Magic.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Shikra: Unleashing Multimodal LLM's Referential Dialogue Magic

Reference 8

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Observation 5eb4c32d-f262-4321-8e27-7fbdae07ad64 · outbound

This paper cites Internvl: Scaling up vision foundation mod- els and aligning for generic visual-linguistic tasks.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Internvl: Scaling up vision foundation mod- els and aligning for generic visual-linguistic tasks

Reference 9

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Observation fe416e7f-c5ba-4648-9501-e4e7818801cb · outbound

This paper cites Pra-net: Point relation-aware network for 3d point cloud analysis.IEEE TIP, 30:4436–4448, 2021.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Pra-net: Point relation-aware network for 3d point cloud analysis.IEEE TIP, 30:4436–4448, 2021

Reference 10

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Observation cae22099-756b-4a79-ae48-34d4b763b966 · outbound

This paper cites Abo: Dataset and benchmarks for real-world 3d object un- derstanding.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Abo: Dataset and benchmarks for real-world 3d object un- derstanding

Reference 11

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Observation 8c13730c-450c-4356-a4b1-c9c1ad63dfa5 · outbound

This paper cites Siamese cnn-bilstm architecture for 3d shape representation learning.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Siamese cnn-bilstm architecture for 3d shape representation learning

Reference 12

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Observation f48d7503-23da-495c-9c5c-1ca5fc3aaaf0 · outbound

This paper cites Objaverse: A universe of annotated 3d objects.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Objaverse: A universe of annotated 3d objects

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:14.802001Z

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Observation fc43a5cb-36cb-4c0f-adff-13eabd631bfa · outbound

This paper cites Equivariant multi-view networks.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Equivariant multi-view networks

Reference 14

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Observation 2495eeda-fb6a-4edf-9f30-bbecd515182c · outbound

This paper cites Gvcnn: Group-view convolutional neural networks for 3d shape recognition.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Gvcnn: Group-view convolutional neural networks for 3d shape recognition

Reference 15

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Observation 1a816f62-9280-4509-8bfc-ac887bb3fe15 · outbound

This paper cites Meshnet: Mesh neural network for 3d shape rep- resentation.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Meshnet: Mesh neural network for 3d shape rep- resentation

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:14.783681Z

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Observation f4b2d03c-7c35-4a48-9b51-6edd2ecf2adc · outbound

This paper cites Shrec’22 track: Open-set 3d object retrieval.Computers & Graphics, 107:231–240, 2022.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Shrec’22 track: Open-set 3d object retrieval.Computers & Graphics, 107:231–240, 2022

Reference 17

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Observation 4d4f070d-1df2-4fa2-867c-d24670e22292 · outbound

This paper cites Hypergraph-based multi-modal represen- tation for open-set 3d object retrieval.IEEE TPAMI, 2023.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Hypergraph-based multi-modal represen- tation for open-set 3d object retrieval.IEEE TPAMI, 2023

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:14.768338Z

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Observation bcff649d-f534-48c4-a44d-4bbf168d559c · outbound

This paper cites 3d object retrieval based on similarity calculation in 3d computer aided design systems.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval 3d object retrieval based on similarity calculation in 3d computer aided design systems

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:14.760873Z

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Observation 10d8b2a7-003e-42e0-a19a-46879c8ada4a · outbound

This paper cites Clip-adapter: Better vision-language models with feature adapters.IJCV, 132(2):581–595, 2024.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Clip-adapter: Better vision-language models with feature adapters.IJCV, 132(2):581–595, 2024

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:14.752571Z

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Observation 76847e5b-f7f0-4c99-b861-0e6491b9ae51 · outbound

This paper cites Deep learning for 3d point clouds: A survey.IEEE TPAMI, 43(12):4338–4364, 2020.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Deep learning for 3d point clouds: A survey.IEEE TPAMI, 43(12):4338–4364, 2020

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:14.744371Z

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Observation a962f3c3-cf0f-4410-8616-8d0bc53dfd3d · outbound

This paper cites 3d2seqviews: Aggregating sequential views for 3d global feature learning by cnn with hierarchical attention ag- gregation.IEEE TIP, 28(8):3986–3999, 2019.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval 3d2seqviews: Aggregating sequential views for 3d global feature learning by cnn with hierarchical attention ag- gregation.IEEE TIP, 28(8):3986–3999, 2019

Reference 22

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Observation 88effd1b-bd57-4880-80f8-ad08d88e8368 · outbound

This paper cites Triplet-center loss for multi-view 3d object retrieval.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Triplet-center loss for multi-view 3d object retrieval

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:14.731351Z

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Observation 3dfcf5d2-0e93-49e3-bbaa-ab326a267836 · outbound

This paper cites View n-gram network for 3d object retrieval.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval View n-gram network for 3d object retrieval

Reference 24

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Observation 815893c3-e0a6-4b80-abef-14fc8b3f754c · outbound

This paper cites Latformer: Locality-aware point- view fusion transformer for 3d shape recognition.PR, 151: 110413, 2024.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Latformer: Locality-aware point- view fusion transformer for 3d shape recognition.PR, 151: 110413, 2024

Reference 25

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Observation 37b4c765-2053-4fb8-807c-91540a2c986a · outbound

This paper cites Clip goes 3d: Leveraging prompt tuning for language grounded 3d recognition.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Clip goes 3d: Leveraging prompt tuning for language grounded 3d recognition

Reference 26

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Observation 7386090c-3e0a-4375-9fd0-c1e07f7a3495 · outbound

This paper cites LoRA: Low-rank adaptation of large language models.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval LoRA: Low-rank adaptation of large language models

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:14.701250Z

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Observation 117d2cdc-be8b-4cf3-a377-2cbd543781f4 · outbound

This paper cites Scal- able deep multimodal learning for cross-modal retrieval.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Scal- able deep multimodal learning for cross-modal retrieval

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:14.693541Z

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Observation 4daccc3d-7e4b-4ebc-9ace-3d51d8f055bd · outbound

This paper cites Clip2point: Transfer clip to point cloud classifica- tion with image-depth pre-training.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Clip2point: Transfer clip to point cloud classifica- tion with image-depth pre-training

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:14.685113Z

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Observation 01dbc503-4c9e-4fd6-b786-753e0d282054 · outbound

This paper cites Developing an engineering shape benchmark for cad models.Computer-Aided Design, 38(9):939–953, 2006.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Developing an engineering shape benchmark for cad models.Computer-Aided Design, 38(9):939–953, 2006

Reference 30

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Observation 3cb8bc34-6b35-4991-9fec-1da2e7051ed5 · outbound

This paper cites Cross-modal center loss for 3d cross-modal retrieval.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Cross-modal center loss for 3d cross-modal retrieval

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:14.529357Z

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Observation 1a92f109-709f-4ad2-a78c-e501fd6c3e7b · outbound

This paper cites Rotationnet: Joint object categorization and pose estimation using multiviews from unsupervised viewpoints.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Rotationnet: Joint object categorization and pose estimation using multiviews from unsupervised viewpoints

Reference 32

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Observation 44a49962-a314-47a7-b401-c029592c416c · outbound

This paper cites Rotation invariant spherical harmonic repre- sentation of 3 d shape descriptors.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Rotation invariant spherical harmonic repre- sentation of 3 d shape descriptors

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:14.259037Z

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Observation 9243c747-567d-40b2-b973-5ffb1feeeb1c · outbound

This paper cites Re- search challenges for digital archives of 3d cultural her- itage models.Journal on Computing and Cultural Heritage (JOCCH), 2(3):1–17, 2010.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Re- search challenges for digital archives of 3d cultural her- itage models.Journal on Computing and Cultural Heritage (JOCCH), 2(3):1–17, 2010

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:13.992856Z

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Observation 4ab4e967-f98d-4b2d-a1d5-b3c9b8692492 · outbound

This paper cites Angular triplet- center loss for multi-view 3d shape retrieval.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Angular triplet- center loss for multi-view 3d shape retrieval

Reference 35

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Observation bc8403e9-a325-4f6f-8ae6-c364dcd4624e · outbound

This paper cites Meshmae: Masked autoencoders for 3d mesh data analysis.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Meshmae: Masked autoencoders for 3d mesh data analysis

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:13.736307Z

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Observation 5e48812c-ecfb-49ac-b19d-496b2f16b128 · outbound

This paper cites Improved baselines with visual instruction tuning.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Improved baselines with visual instruction tuning

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:13.482566Z

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Observation 264362b9-fa81-4531-b6c5-7806627be3d0 · outbound

This paper cites Visual instruction tuning.NeurIPS, 36, 2024.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Visual instruction tuning.NeurIPS, 36, 2024

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:13.133129Z

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Observation 8a090f86-d450-4e86-b979-d7a3d59422da · outbound

This paper cites Openshape: Scaling up 3d shape representation towards open-world understanding.NeurIPS, 36, 2023.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Openshape: Scaling up 3d shape representation towards open-world understanding.NeurIPS, 36, 2023

Reference 39

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Observation c71387ad-3397-4a1b-96cc-a86cebe9f79f · outbound

This paper cites Point2sequence: Learning the shape representa- tion of 3d point clouds with an attention-based sequence to sequence network.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Point2sequence: Learning the shape representa- tion of 3d point clouds with an attention-based sequence to sequence network

Reference 40

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Observation 387e2f23-ae6f-4852-91fb-4a6812ffd73a · outbound

This paper cites Relation-shape convolutional neural network for point cloud analysis.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Relation-shape convolutional neural network for point cloud analysis

Reference 41

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Observation 4e2d60e5-80c3-4e40-92a4-26d27bc026b4 · outbound

This paper cites An Empirical Study of Scaling Instruct-Tuned Large Multimodal Models.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval An Empirical Study of Scaling Instruct-Tuned Large Multimodal Models

Reference 42

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Observation 0315681a-189f-43f7-a31b-854b87843fc2 · outbound

This paper cites 3d learning objects for augmented/virtual reality educational ecosystems.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval 3d learning objects for augmented/virtual reality educational ecosystems

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:12.619734Z

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Observation bb366d37-50fe-4ac3-8559-cc8366f9941c · outbound

This paper cites V oxnet: A 3d con- volutional neural network for real-time object recognition.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval V oxnet: A 3d con- volutional neural network for real-time object recognition

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:12.433140Z

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Observation 16e478c5-a186-41a6-9a3c-e69da20444fb · outbound

This paper cites Mmjn: Multi-modal joint networks for 3d shape recognition.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Mmjn: Multi-modal joint networks for 3d shape recognition

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:12.273646Z

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Observation 30ad683e-6621-4b01-bd3f-c78dfdf80f9f · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Representation Learning with Contrastive Predictive Coding

Reference 46

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Observation 4fcbc6c2-0bbd-44ee-bec3-5f48dbc128ec · outbound

This paper cites Kosmos-2: Grounding Multimodal Large Language Models to the World.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Kosmos-2: Grounding Multimodal Large Language Models to the World

Reference 47

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Observation c7c831b5-0ae5-464f-9eaa-86b921d388a5 · outbound

This paper cites Pointnet: Deep learning on point sets for 3d classification and segmentation.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Pointnet: Deep learning on point sets for 3d classification and segmentation

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-06T12:47:06.016588Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8029e1ed-a18e-4386-ac80-e70f2aabe21a · outbound

This paper cites Pointnet++: Deep hierarchical feature learning on point sets in a metric space.NeurIPS, 30, 2017.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Pointnet++: Deep hierarchical feature learning on point sets in a metric space.NeurIPS, 30, 2017

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-06T12:47:06.111380Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d8739b54-3665-4a47-b467-36176d8b2325 · outbound

This paper cites Learn- ing transferable visual models from natural language super- vision.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Learn- ing transferable visual models from natural language super- vision

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:12.064361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation dc8afc3f-b0ee-46a0-8976-33c0606fed60 · outbound

This paper cites Clip for all things zero-shot sketch-based image retrieval, fine- grained or not.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Clip for all things zero-shot sketch-based image retrieval, fine- grained or not

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:11.906256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation bda63105-a27b-41c7-a280-a5f7059b94f3 · outbound

This paper cites Deep- voxels: Learning persistent 3d feature embeddings.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Deep- voxels: Learning persistent 3d feature embeddings

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-06T12:47:06.406724Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 093cc193-e569-423b-bba7-a872a33dc293 · outbound

This paper cites MV-CLIP: Multi-View CLIP for Zero-shot 3D Shape Recognition.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval MV-CLIP: Multi-View CLIP for Zero-shot 3D Shape Recognition

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-06T12:47:06.495224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09ecf3ad-d5ec-4928-bba1-82ec6115d2f7 · outbound

This paper cites Multi-view convolutional neural networks for 3d shape recognition.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Multi-view convolutional neural networks for 3d shape recognition

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:11.726653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e7c38b4e-a674-400a-9ecb-4b353a3fbb1a · outbound

This paper cites A survey of content based 3d shape retrieval methods.Proceedings Shape Modeling Applications, 2004., pages 145–156, 2004.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval A survey of content based 3d shape retrieval methods.Proceedings Shape Modeling Applications, 2004., pages 145–156, 2004

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:11.555829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation ff79b94f-e89e-434f-93ce-072747635032 · outbound

This paper cites O-cnn: Octree-based convolutional neural networks for 3d shape analysis.ACM TOG, 36(4):1–11,.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval O-cnn: Octree-based convolutional neural networks for 3d shape analysis.ACM TOG, 36(4):1–11,

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-06T12:47:06.823291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a403d6d1-6d31-47a6-a48e-6014de054a3b · outbound

This paper cites The All-Seeing Project: Towards Panoptic Visual Recognition and Understanding of the Open World.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval The All-Seeing Project: Towards Panoptic Visual Recognition and Understanding of the Open World

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-06T12:47:06.899224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e314d4b6-7a1d-4cc5-a012-1192015977bc · outbound

This paper cites Visionllm: Large language model is also an open- ended decoder for vision-centric tasks.NeurIPS, 36, 2024.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Visionllm: Large language model is also an open- ended decoder for vision-centric tasks.NeurIPS, 36, 2024

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:11.375033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1380f257-583f-429f-9251-464e7b45e0d7 · outbound

This paper cites Dynamic graph cnn for learning on point clouds.ACM TOG, 38(5): 1–12, 2019.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Dynamic graph cnn for learning on point clouds.ACM TOG, 38(5): 1–12, 2019

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-06T12:47:07.080674Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c94a750d-7e34-4468-93b5-fbe661deca4c · outbound

This paper cites Teda: Boosting vision-lanuage models for zero-shot 3d object retrieval via testing-time distribution alignment.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Teda: Boosting vision-lanuage models for zero-shot 3d object retrieval via testing-time distribution alignment

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:11.173636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d7f9ed69-099a-468d-876a-b5a4a4f2abc6 · outbound

This paper cites View-gcn: View-based graph convolutional network for 3d shape analysis.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval View-gcn: View-based graph convolutional network for 3d shape analysis

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-06T12:47:07.221969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85db8e0f-ccce-4c71-b8e5-487058e71b2e · outbound

This paper cites Multi- modal semantic autoencoder for cross-modal retrieval.Neu- rocomputing, 331:165–175, 2019.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Multi- modal semantic autoencoder for cross-modal retrieval.Neu- rocomputing, 331:165–175, 2019

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:11.027826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 275c8697-f4eb-44d6-a860-a909dc8abef6 · outbound

This paper cites 3d shapenets: A deep representation for volumetric shapes.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval 3d shapenets: A deep representation for volumetric shapes

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:10.885400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation fca0dbe6-d017-462c-a767-61c1cd11760a · outbound

This paper cites Ulip: Learning a unified representation of language, images, and point clouds for 3d understanding.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Ulip: Learning a unified representation of language, images, and point clouds for 3d understanding

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:10.685990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation ae7e5cdc-a3e6-4b3b-bd74-2ecaf4757c92 · outbound

This paper cites Ulip-2: Towards scal- able multimodal pre-training for 3d understanding.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Ulip-2: Towards scal- able multimodal pre-training for 3d understanding

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:10.425943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 89ddbaee-7950-45b1-af27-331e577b8107 · outbound

This paper cites Tip-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Tip-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-06T12:47:07.732480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8df5b5d-f60d-4d5e-8225-a4105bb3babe · outbound

This paper cites Pointclip: Point cloud understanding by clip.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Pointclip: Point cloud understanding by clip

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:10.117082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 05b9e1ca-ef95-4da3-b4f4-2028089a2c1e · outbound

This paper cites Pointweb: Enhancing local neighborhood features for point cloud processing.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Pointweb: Enhancing local neighborhood features for point cloud processing

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-06T12:47:07.936148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f10a92bd-5966-4dc6-8d42-9d3c9d6401a6 · outbound

This paper cites Multi-channel weight-sharing autoencoder based on cascade multi-head attention for multimodal emo- tion recognition.IEEE TMM, 2022.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Multi-channel weight-sharing autoencoder based on cascade multi-head attention for multimodal emo- tion recognition.IEEE TMM, 2022

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:09.781355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e481f9f8-bba0-40ff-a853-2e15e11a0493 · outbound

This paper cites Learn- ing placeholders for open-set recognition.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Learn- ing placeholders for open-set recognition

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:09.475429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 28f81f8b-4d9b-48af-8aed-88c93bcbcdff · outbound

This paper cites Uni3d: Exploring unified 3d representation at scale.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Uni3d: Exploring unified 3d representation at scale

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:09.202898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 45e08547-3a65-4d11-af5e-f1a239455cb7 · outbound

This paper cites Conditional prompt learning for vision-language models.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval Conditional prompt learning for vision-language models

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:08.939053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 99ffab05-b885-4d1f-8e5d-d0f8446993a1 · outbound

This paper cites a synthetic 3D model view of [cls] with different an- gles.

Describe, Adapt and Combine: Empowering CLIP Encoders for Open-set 3D Object Retrieval a synthetic 3D model view of [cls] with different an- gles

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:47:08.708015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers