Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction | Paper Citation Record

Observation 5499e0fd-d72c-41a8-8cfe-7c7e95dcc2bd · outbound

This paper cites DETReg: Unsupervised pretraining with region priors for object detection.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction DETReg: Unsupervised pretraining with region priors for object detection

Reference 1

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Observation ff37da67-598c-4117-8b86-29b5db981143 · outbound

This paper cites Unsu- pervised learning of visual features by contrasting cluster assignments.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Unsu- pervised learning of visual features by contrasting cluster assignments

Reference 2

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Observation 1ea52b99-6f01-49bc-83d4-7a8a740d356f · outbound

This paper cites MMDetection: Open MMLab Detection Toolbox and Benchmark.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction MMDetection: Open MMLab Detection Toolbox and Benchmark

Reference 3

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Observation bec7e1cb-cc47-4cab-b9e5-47cb0bed2860 · outbound

This paper cites Big Self-Supervised Models are Strong Semi-Supervised Learners.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Big Self-Supervised Models are Strong Semi-Supervised Learners

Reference 4

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Observation b028e962-2747-4b83-837d-29c09ec33651 · outbound

This paper cites Improved Baselines with Momentum Contrastive Learning.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Improved Baselines with Momentum Contrastive Learning

Reference 5

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Observation 3fbb1fcf-8f00-4998-b714-a7aa446ed0d8 · outbound

This paper cites Siamese DETR.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Siamese DETR

Reference 6

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Observation 3ab2e7db-8308-4a63-8203-867ecc095c53 · outbound

This paper cites UP-DETR: Unsupervised pre-training for object detection with transformers.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction UP-DETR: Unsupervised pre-training for object detection with transformers

Reference 7

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Observation 1dcd87b9-4aab-48ff-ad3a-24d4a2dcad70 · outbound

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

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction ImageNet: A large-scale hierarchical image database

Reference 8

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Observation 0c8bb856-f8ac-40ca-9d45-7a25bb414c16 · outbound

This paper cites Exploring classification equilibrium in long-tailed object detection.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Exploring classification equilibrium in long-tailed object detection

Reference 9

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Observation 062d9ac1-acf7-466a-8c09-efdd0ae1e134 · outbound

This paper cites Bootstrap your own latent - a new approach to self- supervised learning.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Bootstrap your own latent - a new approach to self- supervised learning

Reference 10

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Observation 575d3ee0-adca-4bbf-98b1-e33efe0bc1d6 · outbound

This paper cites LVIS: A dataset for large vocabulary instance segmentation.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction LVIS: A dataset for large vocabulary instance segmentation

Reference 11

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Observation ff1a40ce-52f6-4bbd-a203-0c049430b577 · outbound

This paper cites Masked autoencoders are scalable vision learners.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Masked autoencoders are scalable vision learners

Reference 12

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Observation 4b7d6f72-bd6f-40f2-ace6-8dbcc3bcb0eb · outbound

This paper cites Momentum contrast for unsupervised visual representation learning.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Momentum contrast for unsupervised visual representation learning

Reference 13

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Observation 0d8d7b83-f8e1-428f-89a8-32a0c476ddc5 · outbound

This paper cites Mask R-CNN.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Mask R-CNN

Reference 14

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Observation 60802ebc-4544-475e-adce-e1f6dd105cfc · outbound

This paper cites Spatial pyramid pooling in deep convolutional networks for visual recognition.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Spatial pyramid pooling in deep convolutional networks for visual recognition

Reference 15

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Observation d481976d-f55d-4881-a45f-a3c1d5667b5c · outbound

This paper cites Deep residual learning for image recognition.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Deep residual learning for image recognition

Reference 16

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Observation 511f1032-921a-4d26-95ed-bb18f80eabb7 · outbound

This paper cites Relieving long-tailed instance segmentation via pairwise class balance.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Relieving long-tailed instance segmentation via pairwise class balance

Reference 17

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Observation 921eca99-3f11-4d71-9b79-44c35e2f8e6e · outbound

This paper cites Efficient visual pretraining with contrastive detection.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Efficient visual pretraining with contrastive detection

Reference 18

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Observation df61836e-2567-48d1-b893-c8a76b6b8a88 · outbound

This paper cites DropLoss for long-tail instance segmentation.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction DropLoss for long-tail instance segmentation

Reference 19

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Observation c1615d84-ec02-497d-9798-a6d1a604c2f6 · outbound

This paper cites An asymmetric augmented self-supervised learning method for unsupervised fine-grained image hashing.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction An asymmetric augmented self-supervised learning method for unsupervised fine-grained image hashing

Reference 20

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Observation 34faf0b2-2742-48f6-91d9-c2a86c3faec5 · outbound

This paper cites The Low-Rank Simplicity Bias in Deep Networks.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction The Low-Rank Simplicity Bias in Deep Networks

Reference 21

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Observation 69638469-3654-4025-9926-cc71919a31d8 · outbound

This paper cites Long-tail detection with effective class-margins.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Long-tail detection with effective class-margins

Reference 22

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Observation 5cd46da6-34ef-4877-a0cf-c4c943dac9c7 · outbound

This paper cites Batch normalization: Accelerating deep network training by reducing internal covariate shift.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Batch normalization: Accelerating deep network training by reducing internal covariate shift

Reference 23

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Observation 519961e5-d943-437d-90a9-e9006e68367f · outbound

This paper cites Learning open-world object proposals without learning to classify.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Learning open-world object proposals without learning to classify

Reference 24

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Observation b29dfd72-9273-4234-a2d0-acf627d845de · outbound

This paper cites AlignDet: Aligning pre-training and fine-tuning in object detection.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction AlignDet: Aligning pre-training and fine-tuning in object detection

Reference 25

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Observation 599ab222-977c-415b-8e48-bbcaba4735c8 · outbound

This paper cites Contrastive learning of person-independent representations for facial action unit detection.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Contrastive learning of person-independent representations for facial action unit detection

Reference 26

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Observation 6f26b01e-b439-4d08-937c-8183d02b7c08 · outbound

This paper cites Overcoming classifier imbalance for long-tail object detection with balanced group softmax.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Overcoming classifier imbalance for long-tail object detection with balanced group softmax

Reference 27

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Observation 9521e0b1-f0ec-4632-b902-4f8219556df9 · outbound

This paper cites Learning representations for facial actions from unlabeled videos.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Learning representations for facial actions from unlabeled videos

Reference 28

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Observation 0014f266-9edb-4adb-bd65-27f96a1013a4 · outbound

This paper cites Occlusion aware facial expression recognition using cnn with attention mechanism.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Occlusion aware facial expression recognition using cnn with attention mechanism

Reference 29

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Observation 06aaf6f3-62b5-4158-9a7a-9b1298a5e3f7 · outbound

This paper cites Self-supervised representation learning from videos for facial action unit detection.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Self-supervised representation learning from videos for facial action unit detection

Reference 30

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Observation fcaf7107-70af-42cf-ac87-52754adefc80 · outbound

This paper cites Feature pyramid networks for object detection.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Feature pyramid networks for object detection

Reference 31

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Observation 59f11c9d-396a-40c8-9b30-804e66778ccc · outbound

This paper cites Focal loss for dense object detection.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Focal loss for dense object detection

Reference 32

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Observation ccf26376-b3ca-4339-9b80-4e1245a51b95 · outbound

This paper cites Microsoft COCO: Common objects in context.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Microsoft COCO: Common objects in context

Reference 33

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Observation a4a5e356-b62f-4b55-87dd-f0e737cd34d0 · outbound

This paper cites Self-EMD: Self-Supervised Object Detection without ImageNet.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Self-EMD: Self-Supervised Object Detection without ImageNet

Reference 34

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Observation 057f361b-b3fc-455f-9a88-7d99c539fcd6 · outbound

This paper cites Rectified linear units improve restricted boltzmann machines.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Rectified linear units improve restricted boltzmann machines

Reference 35

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Observation a1c71737-e94c-41e7-8be0-c6badf35182d · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Representation Learning with Contrastive Predictive Coding

Reference 36

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Observation 925f9e0d-c361-4958-bc00-bc62024d4db1 · outbound

This paper cites Yang, Zach DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Yang, Zach DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala

Reference 37

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Observation 5129edd9-1c76-480b-97d7-97e4ce3b9e2e · outbound

This paper cites Balanced classification: A unified framework for long-tailed object detection.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Balanced classification: A unified framework for long-tailed object detection

Reference 38

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Observation 37dbc27e-89e0-4ffd-a0b9-7b5d7c441239 · outbound

This paper cites You only look once: Unified, real-time object detection.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction You only look once: Unified, real-time object detection

Reference 39

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Observation 8d4c9072-8196-4757-b6c0-ed29387362cf · outbound

This paper cites Faster R-CNN: Towards real-time object detection with region proposal networks.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Faster R-CNN: Towards real-time object detection with region proposal networks

Reference 40

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Observation d655e454-0049-4bd5-ab7c-f9b9f3b2e3e7 · outbound

This paper cites The pitfalls of simplicity bias in neural networks.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction The pitfalls of simplicity bias in neural networks

Reference 41

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Observation c5c09508-891b-4f6e-b5a0-364157b99bb7 · outbound

This paper cites Equalization loss v2: A new gradient balance approach for long-tailed object detection.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Equalization loss v2: A new gradient balance approach for long-tailed object detection

Reference 42

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Observation c9fd8b39-f9ca-4b77-9389-0c08b8c1f117 · outbound

This paper cites Equalization loss for long-tailed object recognition.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Equalization loss for long-tailed object recognition

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:44:50.920965Z

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Observation c31b69ba-af6a-4f6e-b876-f0f24b4a2856 · outbound

This paper cites Evading the simplicity bias: Training a diverse set of models discovers solutions with superior ood generalization.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Evading the simplicity bias: Training a diverse set of models discovers solutions with superior ood generalization

Reference 44

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Observation 416a9e7d-4171-4918-8ac5-c565f7b0c6c2 · outbound

This paper cites Seesaw loss for long-tailed instance segmentation.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Seesaw loss for long-tailed instance segmentation

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:44:50.873408Z

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Observation 656ae487-abb5-4cc0-a7a8-c385a2d47e55 · outbound

This paper cites Contrastive learning based hybrid networks for long-tailed image classification.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Contrastive learning based hybrid networks for long-tailed image classification

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:44:50.849705Z

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Observation 7087f386-31da-4fdb-abdc-1d3d91496d0c · outbound

This paper cites The devil is in classification: A simple framework for long-tail instance segmentation.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction The devil is in classification: A simple framework for long-tail instance segmentation

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:44:50.821650Z

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Observation 5494b0ac-c649-4ed2-8b0a-227236b72496 · outbound

This paper cites Adaptive class suppression loss for long-tail object detection.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Adaptive class suppression loss for long-tail object detection

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:44:50.795325Z

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Observation 85ac17fd-5ad0-46fb-be34-7199cd75a345 · outbound

This paper cites Dense contrastive learning for self-supervised visual pre-training.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Dense contrastive learning for self-supervised visual pre-training

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:44:50.775409Z

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Observation d8d42828-5021-498e-b18a-eead9b1fa88f · outbound

This paper cites Aligning pretraining for detection via object-level contrastive learning.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Aligning pretraining for detection via object-level contrastive learning

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:44:50.754506Z

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This paper cites Attribute-aware deep hashing with self-consistency for large-scale fine-grained image retrieval.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Attribute-aware deep hashing with self-consistency for large-scale fine-grained image retrieval

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:44:50.731397Z

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Observation 9ad9ae2d-b556-4441-80ee-dfa5cfaaaba5 · outbound

This paper cites Delving Deep into Simplicity Bias for Long-Tailed Image Recognition.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Delving Deep into Simplicity Bias for Long-Tailed Image Recognition

Reference 52

Resolution: verified exact; local_arxiv, observed 2026-08-12T20:44:50.322045Z

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Observation 6eb9012b-ab3a-484a-9c11-df3fe20ade2f · outbound

This paper cites Negatives make a positive: An embarrassingly simple approach to semi-supervised few-shot learning.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Negatives make a positive: An embarrassingly simple approach to semi-supervised few-shot learning

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:44:50.709319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c5b7fa1b-3a50-4578-8dc5-ca289dfb6949 · outbound

This paper cites Prototype-based classifier learning for long-tailed visual recognition.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Prototype-based classifier learning for long-tailed visual recognition

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:44:50.688491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a8476e14-bed2-48b7-bf98-6fc0cd11f9df · outbound

This paper cites Self-supervised visual representation learning with semantic grouping.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Self-supervised visual representation learning with semantic grouping

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:44:50.663245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d2a1e448-4ec2-45c2-8345-62309ede8d3a · outbound

This paper cites Instance-Aware Repeat Factor Sampling for Long-Tailed Object Detection.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Instance-Aware Repeat Factor Sampling for Long-Tailed Object Detection

Reference 56

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Source-reported events for the cited work

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Observation e0190a4d-87fe-48bd-bb60-4165b21824f1 · outbound

This paper cites A survey on long-tailed visual recognition.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction A survey on long-tailed visual recognition

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:44:50.641004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1895e2ae-0a9e-4191-8ce7-a8bb3bb2fe3a · outbound

This paper cites Reconciling object-level and global-level objectives for long-tail detection.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Reconciling object-level and global-level objectives for long-tail detection

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:44:50.623296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f42f0652-6bd8-45e8-9e06-b03fc9cd294c · outbound

This paper cites an unresolved cited work.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Unresolved cited work

Reference 59

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:44:50.604471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d552b8e6-083c-401e-8ab9-e6634efb49df · outbound

This paper cites Self-supervised aggregation of diverse experts for test-agnostic long-tailed recognition.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Self-supervised aggregation of diverse experts for test-agnostic long-tailed recognition

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:44:50.583418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 749bfdc3-b121-40b7-98a4-afdacc18caa3 · outbound

This paper cites Deep long-tailed learning: A survey.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Deep long-tailed learning: A survey

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:44:50.559361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 71cf9150-0568-4b70-a72f-58ee5b57b47f · outbound

This paper cites BBN: Bilateral-branch network with cumulative learning for long-tailed visual recognition.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction BBN: Bilateral-branch network with cumulative learning for long-tailed visual recognition

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:44:50.536293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation aae61d55-5cb9-4ae0-ab32-5e3f41f2785f · outbound

This paper cites Generalized logit adjustment: Calibrating fine-tuned models by removing label bias in foundation models.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Generalized logit adjustment: Calibrating fine-tuned models by removing label bias in foundation models

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:44:50.514465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ed7a99f2-a751-4d6e-9350-eb4e84120bd2 · outbound

This paper cites Balanced contrastive learning for long-tailed visual recognition.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Balanced contrastive learning for long-tailed visual recognition

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:44:50.492498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0bc5363d-1275-43ac-b2a6-c9dcf09f32a0 · outbound

This paper cites an unresolved cited work.

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction Unresolved cited work

Reference 256

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:44:50.470740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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