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Robust Object Detection

A Benchmark for the: Robustness of Object Detection Models to Image Corruptions and Distortions

To allow fair comparison of robustness enhancing methods all models have to use a standard ResNet50 backbone because performance strongly scales with backbone capacity. If requested an unrestricted category can be added later.

Benchmark Homepage: https://github.com/bethgelab/robust-detection-benchmark

Metrics:

mPC [AP]: Mean Performance under Corruption [measured in AP]

rPC [%]: Relative Performance under Corruption [measured in %]

Test sets: Coco: val 2017; Pascal VOC: test 2007; Cityscapes: val;

( Image credit: Benchmarking Robustness in Object Detection )

Papers

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Showing 76–90 of 90 papers

TitleStatusHype
Modelling Observation Correlations for Active Exploration and Robust Object Detection—0
Multimodal Object Detection using Depth and Image Data for Manufacturing Parts—0
Multi-Target Domain Adaptation via Unsupervised Domain Classification for Weather Invariant Object Detection—0
WS-DETR: Robust Water Surface Object Detection through Vision-Radar Fusion with Detection Transformer—0
Multi-Task Cross-Modality Attention-Fusion for 2D Object Detection—0
UAV3D: A Large-scale 3D Perception Benchmark for Unmanned Aerial Vehicles—0
SRCD: Semantic Reasoning with Compound Domains for Single-Domain Generalized Object Detection—0
Proposal Learning for Semi-Supervised Object Detection—0
UAV Cognitive Semantic Communications Enabled by Knowledge Graph for Robust Object Detection—0
A Semantic Consistency Feature Alignment Object Detection Model Based on Mixed-Class Distribution Metrics—0
RestoreX-AI: A Contrastive Approach towards Guiding Image Restoration via Explainable AI Systems—0
RobuRCDet: Enhancing Robustness of Radar-Camera Fusion in Bird's Eye View for 3D Object Detection—0
Uncertainty-Encoded Multi-Modal Fusion for Robust Object Detection in Autonomous Driving—0
Exploring Thermal Images for Object Detection in Underexposure Regions for Autonomous Driving—0
Weakly Aligned Feature Fusion for Multimodal Object Detection—0
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