SOTAVerified

Long-tailed Object Detection

The training dataset obeys a long-tailed distribution, i.e., the head categories occupy most samples whereas the tail categories only own a few samples. However, the testing dataset is balanced across categories.

Papers

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Showing 1–25 of 25 papers

TitleStatusHype
DINO-X: A Unified Vision Model for Open-World Object Detection and UnderstandingCode5
Equalized Focal Loss for Dense Long-Tailed Object DetectionCode2
The Equalization Losses: Gradient-Driven Training for Long-tailed Object RecognitionCode2
Towards Resolving the Challenge of Long-tail Distribution in UAV Images for Object DetectionCode1
On Model Calibration for Long-Tailed Object Detection and Instance SegmentationCode1
MosaicOS: A Simple and Effective Use of Object-Centric Images for Long-Tailed Object DetectionCode1
Exploring Classification Equilibrium in Long-Tailed Object DetectionCode1
Balanced Classification: A Unified Framework for Long-Tailed Object DetectionCode1
Forest R-CNN: Large-Vocabulary Long-Tailed Object Detection and Instance SegmentationCode1
Towards All-in-one Pre-training via Maximizing Multi-modal Mutual InformationCode1
Equalization Loss v2: A New Gradient Balance Approach for Long-tailed Object DetectionCode1
SimLTD: Simple Supervised and Semi-Supervised Long-Tailed Object DetectionCode1
Long-tail Detection with Effective Class-MarginsCode1
Adaptive Hierarchical Representation Learning for Long-Tailed Object Detection—0
Boosting Long-tailed Object Detection via Step-wise Learning on Smooth-tail Data—0
Exponentially Weighted Instance-Aware Repeat Factor Sampling for Long-Tailed Object Detection Model Training in Unmanned Aerial Vehicles Surveillance Scenarios—0
Instance-Aware Repeat Factor Sampling for Long-Tailed Object Detection—0
Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction—0
Pursuing Better Decision Boundaries for Long-Tailed Object Detection via Category Information Amount—0
Rectify the Regression Bias in Long-Tailed Object Detection—0
Semi-Supervised and Long-Tailed Object Detection with CascadeMatchCode0
Learning from Rich Semantics and Coarse Locations for Long-tailed Object DetectionCode0
Improving Long-tailed Object Detection with Image-Level Supervision by Multi-Task Collaborative LearningCode0
Fractal Calibration for long-tailed object detectionCode0
Consensus Focus for Object Detection and minority classesCode0
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