Instance-Level Generation for Representation Learning | Paper Citation Record

Observation d0030d60-c284-45d2-b568-2f9343a319cd · outbound

This paper cites Augmented reality meets computer vision: Efficient data generation for urban driving scenes.

Instance-Level Generation for Representation Learning Augmented reality meets computer vision: Efficient data generation for urban driving scenes

Reference 1

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Observation 96ffab71-e94e-424b-a320-890cc29b481c · outbound

This paper cites Unicom: Universal and compact representation learning for image retrieval.

Instance-Level Generation for Representation Learning Unicom: Universal and compact representation learning for image retrieval

Reference 2

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Observation 02ac6ad2-5f73-4f9c-825b-4732c761d861 · outbound

This paper cites This dataset does not exist: training models from generated images.

Instance-Level Generation for Representation Learning This dataset does not exist: training models from generated images

Reference 3

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Observation 7139e9be-8bd5-432d-b8ae-b742cee7bda7 · outbound

This paper cites Large scale gan training for high fidelity natural image synthesis.

Instance-Level Generation for Representation Learning Large scale gan training for high fidelity natural image synthesis

Reference 4

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Observation aa17a730-d1cb-4150-ae83-6c217830a664 · outbound

This paper cites Ove6d: Object viewpoint encoding for depth-based 6d object pose estimation.

Instance-Level Generation for Representation Learning Ove6d: Object viewpoint encoding for depth-based 6d object pose estimation

Reference 5

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Observation 72c352ae-f7e6-40cf-b527-03e96a0b45ac · outbound

This paper cites Unifying deep local and global features for image search.

Instance-Level Generation for Representation Learning Unifying deep local and global features for image search

Reference 6

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Observation d4e97668-46f9-4976-9d2b-75ae81eba570 · outbound

This paper cites ShapeNet: An Information-Rich 3D Model Repository.

Instance-Level Generation for Representation Learning ShapeNet: An Information-Rich 3D Model Repository

Reference 7

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Observation d3de06a8-4c09-43a5-aa59-7ac8138cff9d · outbound

This paper cites A simple framework for contrastive learning of visual representations.

Instance-Level Generation for Representation Learning A simple framework for contrastive learning of visual representations

Reference 8

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Observation 92571c47-3be7-4458-b353-2f2bb04d9985 · outbound

This paper cites Pali: A jointly-scaled multilingual language-image model.

Instance-Level Generation for Representation Learning Pali: A jointly-scaled multilingual language-image model

Reference 9

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Observation 55a6289e-6b3d-4a33-b67c-fe809d5e317d · outbound

This paper cites Learning semantic segmentation from synthetic data: A geometrically guided input-output adaptation approach.

Instance-Level Generation for Representation Learning Learning semantic segmentation from synthetic data: A geometrically guided input-output adaptation approach

Reference 10

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Observation 53f18c40-aaa0-4b65-b906-bd293be4ec28 · outbound

This paper cites Learning a similarity metric discriminatively, with application to face verification.

Instance-Level Generation for Representation Learning Learning a similarity metric discriminatively, with application to face verification

Reference 11

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Observation 36522683-9c1f-48bc-a9bb-dcc4af599701 · outbound

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

Instance-Level Generation for Representation Learning Objaverse: A universe of annotated 3d objects

Reference 12

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Observation b7f9f8dd-f321-482b-919d-d337112f1b30 · outbound

This paper cites Arcface: Additive angular margin loss for deep face recognition.

Instance-Level Generation for Representation Learning Arcface: Additive angular margin loss for deep face recognition

Reference 13

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Observation 3703c512-0d4a-46f4-bb07-148d77f73a9c · outbound

This paper cites ImageNet : A large-scale hierarchical image database.

Instance-Level Generation for Representation Learning ImageNet : A large-scale hierarchical image database

Reference 14

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Observation 9cecbac1-bc71-463e-8940-bece37083d0c · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

Instance-Level Generation for Representation Learning An image is worth 16x16 words: Transformers for image recognition at scale

Reference 15

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Observation e4c5ec77-f5b0-4e44-bcdb-48ff74ef6fe4 · outbound

This paper cites Cut, paste and learn: Surprisingly easy synthesis for instance detection.

Instance-Level Generation for Representation Learning Cut, paste and learn: Surprisingly easy synthesis for instance detection

Reference 16

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Observation 098e2139-37f8-48fa-9caa-304b4c58f3bd · outbound

This paper cites The group loss for deep metric learning.

Instance-Level Generation for Representation Learning The group loss for deep metric learning

Reference 17

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Observation 5c61bcc5-6c99-4d1c-ad45-808cccd51558 · outbound

This paper cites Scaling laws of synthetic images for model training.

Instance-Level Generation for Representation Learning Scaling laws of synthetic images for model training

Reference 18

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Observation aa7599fb-ef35-443c-bbf8-62485f6a30b1 · outbound

This paper cites Instructdiffusion: A generalist modeling interface for vision tasks.

Instance-Level Generation for Representation Learning Instructdiffusion: A generalist modeling interface for vision tasks

Reference 19

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Observation 6df2a2f3-158f-4ba1-92c5-e119cf8b9f55 · outbound

This paper cites Synthesizing Training Data for Object Detection in Indoor Scenes.

Instance-Level Generation for Representation Learning Synthesizing Training Data for Object Detection in Indoor Scenes

Reference 20

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Observation 01fd1472-ef12-4bb9-9103-66ec3782c742 · outbound

This paper cites Revisiting the fisher vector for fine-grained classification.

Instance-Level Generation for Representation Learning Revisiting the fisher vector for fine-grained classification

Reference 21

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Observation a3e0034e-8ec9-4883-b3f0-702bb6a40848 · outbound

This paper cites Dimensionality reduction by learning an invariant mapping.

Instance-Level Generation for Representation Learning Dimensionality reduction by learning an invariant mapping

Reference 22

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Observation c968f2ed-e360-4961-803e-b8ba430b0933 · outbound

This paper cites Deep residual learning for image recognition.

Instance-Level Generation for Representation Learning Deep residual learning for image recognition

Reference 23

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Observation 8d0c8fc1-a737-4b63-9df1-18c4a2f240ac · outbound

This paper cites Momentum contrast for unsupervised visual representation learning.

Instance-Level Generation for Representation Learning Momentum contrast for unsupervised visual representation learning

Reference 24

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Observation 6176a15b-ebde-4e71-a371-b26811d0590e · outbound

This paper cites Local descriptors optimized for average precision.

Instance-Level Generation for Representation Learning Local descriptors optimized for average precision

Reference 25

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Observation 2d44f649-29dc-4f19-9001-e7f8b6af1534 · outbound

This paper cites GPT-4o System Card.

Instance-Level Generation for Representation Learning GPT-4o System Card

Reference 26

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Observation e3d27429-0b7d-4911-8cb5-339911d7cfb8 · outbound

This paper cites Proxy anchor loss for deep metric learning.

Instance-Level Generation for Representation Learning Proxy anchor loss for deep metric learning

Reference 27

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Observation a42a7c18-79dd-4118-a9dd-2f190269a681 · outbound

This paper cites Self-taught metric learning without labels.

Instance-Level Generation for Representation Learning Self-taught metric learning without labels

Reference 28

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Observation 894b2649-e8c7-40b7-b268-45c744cadde2 · outbound

This paper cites Adam: A method for stochastic optimization.

Instance-Level Generation for Representation Learning Adam: A method for stochastic optimization

Reference 29

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Observation f8de048a-74ca-46be-91b3-c013d12c4f70 · outbound

This paper cites ILIAS : Instance-level image retrieval at scale.

Instance-Level Generation for Representation Learning ILIAS : Instance-level image retrieval at scale

Reference 30

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Observation d6530e40-5899-417d-ac89-db6e45548203 · outbound

This paper cites Cross-image-attention for conditional embeddings in deep metric learning.

Instance-Level Generation for Representation Learning Cross-image-attention for conditional embeddings in deep metric learning

Reference 31

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Observation fa83ba6a-386d-4c07-b4d9-acbc54963b9a · outbound

This paper cites Fine-grained recognition without part annotations.

Instance-Level Generation for Representation Learning Fine-grained recognition without part annotations

Reference 32

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Observation 8d51e7bf-759b-4380-add1-b7ec12787f1e · outbound

This paper cites Cosypose: Consistent multi-view multi-object 6d pose estimation.

Instance-Level Generation for Representation Learning Cosypose: Consistent multi-view multi-object 6d pose estimation

Reference 33

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Observation f051707e-0d58-494b-b850-fa88469ca3e8 · outbound

This paper cites Correlation verification for image retrieval.

Instance-Level Generation for Representation Learning Correlation verification for image retrieval

Reference 34

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Observation 8cc7eaab-a97b-4430-a8ae-c1847e8ed834 · outbound

This paper cites Syncdreamer: Generating multiview-consistent images from a single-view image.

Instance-Level Generation for Representation Learning Syncdreamer: Generating multiview-consistent images from a single-view image

Reference 35

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Observation 8ae932fb-ba44-496c-bfcf-fae9e8309f62 · outbound

This paper cites Deepfashion: Powering robust clothes recognition and retrieval with rich annotations.

Instance-Level Generation for Representation Learning Deepfashion: Powering robust clothes recognition and retrieval with rich annotations

Reference 36

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Observation 0ba5e1e1-9f86-4421-a851-1210ff529b45 · outbound

This paper cites Amass: Archive of motion capture as surface shapes.

Instance-Level Generation for Representation Learning Amass: Archive of motion capture as surface shapes

Reference 37

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Observation e2029850-52ef-440e-8040-16feb8274693 · outbound

This paper cites Null-text inversion for editing real images using guided diffusion models.

Instance-Level Generation for Representation Learning Null-text inversion for editing real images using guided diffusion models

Reference 38

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Observation c56c7db5-6a3d-48ff-9033-4f797bb687de · outbound

This paper cites A metric learning reality check.

Instance-Level Generation for Representation Learning A metric learning reality check

Reference 39

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Observation f34247f1-89eb-429e-9074-32189cf702bd · outbound

This paper cites Deep metric learning via lifted structured feature embedding.

Instance-Level Generation for Representation Learning Deep metric learning via lifted structured feature embedding

Reference 40

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Observation 78f1f684-ff52-4a12-8213-c0e9197649c8 · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

Instance-Level Generation for Representation Learning DINOv2: Learning Robust Visual Features without Supervision

Reference 41

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Observation c57194a1-8ae7-475a-967b-6ce2199449fd · outbound

This paper cites Recall@ k surrogate loss with large batches and similarity mixup.

Instance-Level Generation for Representation Learning Recall@ k surrogate loss with large batches and similarity mixup

Reference 42

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Observation 465a7ab3-1335-42cc-99f4-a091974ca336 · outbound

This paper cites RP2K: A Large-Scale Retail Product Dataset for Fine-Grained Image Classification.

Instance-Level Generation for Representation Learning RP2K: A Large-Scale Retail Product Dataset for Fine-Grained Image Classification

Reference 43

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Observation 1cc7f955-bf71-483c-aac9-612cab3e6b88 · outbound

This paper cites Learning deep object detectors from 3d models.

Instance-Level Generation for Representation Learning Learning deep object detectors from 3d models

Reference 44

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Observation 45283332-a9b7-457a-b4f4-0fcbebd4829a · outbound

This paper cites Philbin, O.

Instance-Level Generation for Representation Learning Philbin, O

Reference 45

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Observation ce7dc826-90a6-4e03-9401-f47078a7ba91 · outbound

This paper cites Philbin, O.

Instance-Level Generation for Representation Learning Philbin, O

Reference 46

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Observation c3012e0e-ef2d-4de8-bdc3-6446186fc013 · outbound

This paper cites Softtriple loss: Deep metric learning without triplet sampling.

Instance-Level Generation for Representation Learning Softtriple loss: Deep metric learning without triplet sampling

Reference 47

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Observation cb60489a-2da3-4d46-8c4b-2e9eda9240b8 · outbound

This paper cites Revisiting oxford and paris: Large-scale image retrieval benchmarking.

Instance-Level Generation for Representation Learning Revisiting oxford and paris: Large-scale image retrieval benchmarking

Reference 48

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Observation e6d32c39-1b25-423d-aea8-ff141353ab1f · outbound

This paper cites Learning transferable visual models from natural language supervision.

Instance-Level Generation for Representation Learning Learning transferable visual models from natural language supervision

Reference 49

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Observation db1d954c-8253-44e7-b99e-35fb3930aab4 · outbound

This paper cites Dreambooth3d: Subject-driven text-to-3d generation.

Instance-Level Generation for Representation Learning Dreambooth3d: Subject-driven text-to-3d generation

Reference 50

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Observation 6565ced2-c07b-4069-ae3b-ebb8835703d7 · outbound

This paper cites Robust and decomposable average precision for image retrieval.

Instance-Level Generation for Representation Learning Robust and decomposable average precision for image retrieval

Reference 51

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Observation 2226bceb-4f96-49b6-bf40-23f2db637c69 · outbound

This paper cites Hierarchical average precision training for pertinent image retrieval.

Instance-Level Generation for Representation Learning Hierarchical average precision training for pertinent image retrieval

Reference 52

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Observation 0455821c-c82c-431b-a772-b5cffe9583e8 · outbound

This paper cites Learning with average precision: Training image retrieval with a listwise loss.

Instance-Level Generation for Representation Learning Learning with average precision: Training image retrieval with a listwise loss

Reference 53

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Observation 1f75ffee-546e-4e32-83b8-d421b1fc1f0c · outbound

This paper cites Optimizing rank-based metrics with blackbox differentiation.

Instance-Level Generation for Representation Learning Optimizing rank-based metrics with blackbox differentiation

Reference 54

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Observation 0e9060e0-eb04-4aed-9e98-3e9448ae27d1 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

Instance-Level Generation for Representation Learning High-resolution image synthesis with latent diffusion models

Reference 55

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Observation a039d120-d30e-4022-8f3a-6dd74828b00a · outbound

This paper cites The synthia dataset: A large collection of synthetic images for semantic segmentation of urban scenes.

Instance-Level Generation for Representation Learning The synthia dataset: A large collection of synthetic images for semantic segmentation of urban scenes

Reference 56

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Observation c1682128-3613-4554-a015-cfd7444fc5c6 · outbound

This paper cites Revisiting training strategies and generalization performance in deep metric learning.

Instance-Level Generation for Representation Learning Revisiting training strategies and generalization performance in deep metric learning

Reference 57

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Observation 72fb6ddb-242b-4652-a40c-86f95769d44a · outbound

This paper cites On rendering synthetic images for training an object detector.

Instance-Level Generation for Representation Learning On rendering synthetic images for training an object detector

Reference 58

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Observation dd24cec6-36a9-40d5-98d8-fd4e757c58dd · outbound

This paper cites Imagenet large scale visual recognition challenge.

Instance-Level Generation for Representation Learning Imagenet large scale visual recognition challenge

Reference 59

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Observation c9b8acf7-57fe-4bfb-8abf-fb01f5280c98 · outbound

This paper cites Fake it till you make it: Learning transferable representations from synthetic imagenet clones.

Instance-Level Generation for Representation Learning Fake it till you make it: Learning transferable representations from synthetic imagenet clones

Reference 60

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Observation 89426161-e542-46f6-b2c0-23ce8dd32244 · outbound

This paper cites Adversarial diffusion distillation.

Instance-Level Generation for Representation Learning Adversarial diffusion distillation

Reference 61

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Observation d622a4d2-c55f-4085-ad4c-21bf4d474ba3 · outbound

This paper cites Facenet: A unified embedding for face recognition and clustering.

Instance-Level Generation for Representation Learning Facenet: A unified embedding for face recognition and clustering

Reference 62

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Observation 51a95161-2016-419c-aed8-40e5ebd3d99a · outbound

This paper cites LAION-400M : Open dataset of clip-filtered 400 million image-text pairs.

Instance-Level Generation for Representation Learning LAION-400M : Open dataset of clip-filtered 400 million image-text pairs

Reference 63

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Observation 5baf8eb9-b1f6-45c5-aef2-810ef301a580 · outbound

This paper cites Learning intra-batch connections for deep metric learning.

Instance-Level Generation for Representation Learning Learning intra-batch connections for deep metric learning

Reference 64

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Observation e2c42f50-af6b-4c19-8524-1400621ea81d · outbound

This paper cites Global features are all you need for image retrieval and reranking.

Instance-Level Generation for Representation Learning Global features are all you need for image retrieval and reranking

Reference 65

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Observation 177dd14b-53b7-448c-8e05-cb51aca3acaf · outbound

This paper cites Improved deep metric learning with multi-class n-pair loss objective.

Instance-Level Generation for Representation Learning Improved deep metric learning with multi-class n-pair loss objective

Reference 66

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Observation 62e9646f-5376-4741-9732-c0b236c23c9e · outbound

This paper cites Ames: Asymmetric and memory-efficient similarity estimation for instance-level retrieval.

Instance-Level Generation for Representation Learning Ames: Asymmetric and memory-efficient similarity estimation for instance-level retrieval

Reference 67

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Observation 57db2dd2-9f7e-4b9e-9f3a-9b6ec1dee03f · outbound

This paper cites Personalized representation from personalized generation.

Instance-Level Generation for Representation Learning Personalized representation from personalized generation

Reference 68

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Observation 31001ae9-d604-49cd-a29b-9201ec892a7b · outbound

This paper cites Proxynca++: Revisiting and revitalizing proxy neighborhood component analysis.

Instance-Level Generation for Representation Learning Proxynca++: Revisiting and revitalizing proxy neighborhood component analysis

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-04T10:43:15.540301Z

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Observation d8dbe007-b240-4818-8bf8-2ec172df9273 · outbound

This paper cites Stablerep: Synthetic images from text-to-image models make strong visual representation learners.

Instance-Level Generation for Representation Learning Stablerep: Synthetic images from text-to-image models make strong visual representation learners

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-04T10:43:15.645070Z

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Observation 026b78fe-3729-4693-892b-4f17c370346d · outbound

This paper cites Self6d: Self-supervised monocular 6d object pose estimation.

Instance-Level Generation for Representation Learning Self6d: Self-supervised monocular 6d object pose estimation

Reference 71

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Observation 0c5328fc-65b3-4b6f-b164-b5af9a5df196 · outbound

This paper cites Cosface: Large margin cosine loss for deep face recognition.

Instance-Level Generation for Representation Learning Cosface: Large margin cosine loss for deep face recognition

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-04T10:43:15.758183Z

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Observation aa6b77c7-0fbc-440a-ba79-b889601c6bf1 · outbound

This paper cites Instre: a new benchmark for instance-level object retrieval and recognition.

Instance-Level Generation for Representation Learning Instre: a new benchmark for instance-level object retrieval and recognition

Reference 73

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Observation 83c77028-0f75-4c43-9fdf-be753410c644 · outbound

This paper cites Google landmarks dataset v2 - A large-scale benchmark for instance-level recognition and retrieval.

Instance-Level Generation for Representation Learning Google landmarks dataset v2 - A large-scale benchmark for instance-level recognition and retrieval

Reference 74

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Observation caf43ade-20c5-418d-8d0d-c82665e74c2f · outbound

This paper cites Not only generative art: Stable diffusion for content-style disentanglement in art analysis.

Instance-Level Generation for Representation Learning Not only generative art: Stable diffusion for content-style disentanglement in art analysis

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-04T10:43:15.928050Z

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Observation 3e717f46-d36c-4beb-830a-2d51c44c0002 · outbound

This paper cites The met dataset: Instance-level recognition for artworks.

Instance-Level Generation for Representation Learning The met dataset: Instance-level recognition for artworks

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-04T10:43:16.031851Z

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Observation 53cbe87b-390e-4417-8fce-af7257375f08 · outbound

This paper cites Towards universal image embeddings: A large-scale dataset and challenge for generic image representations.

Instance-Level Generation for Representation Learning Towards universal image embeddings: A large-scale dataset and challenge for generic image representations

Reference 77

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Observation f60a5cc1-c3c5-4ca5-b5d3-5234a754ed17 · outbound

This paper cites Classification is a Strong Baseline for Deep Metric Learning.

Instance-Level Generation for Representation Learning Classification is a Strong Baseline for Deep Metric Learning

Reference 78

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Observation c1a12ad7-3bd8-435d-b4f1-ffe3e686a412 · outbound

This paper cites Sigmoid loss for language image pre-training.

Instance-Level Generation for Representation Learning Sigmoid loss for language image pre-training

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-04T10:43:16.234610Z

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Observation 6e15c70c-377c-4780-949d-3eaef9378a18 · outbound

This paper cites Adding conditional control to text-to-image diffusion models.

Instance-Level Generation for Representation Learning Adding conditional control to text-to-image diffusion models

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-04T10:43:16.333874Z

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Observation 435cad86-e8af-4480-8d62-d2ace0936b80 · outbound

This paper cites Scaling in-the-wild training for diffusion-based illumination harmonization and editing by imposing consistent light transport.

Instance-Level Generation for Representation Learning Scaling in-the-wild training for diffusion-based illumination harmonization and editing by imposing consistent light transport

Reference 81

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