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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 51–90 of 90 papers

TitleStatusHype
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
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
Towards Adversarially Robust Object Detection—0
Robust Object Detection under Occlusion with Context-Aware CompositionalNets—0
Towards Robust Object Detection: Bayesian RetinaNet for Homoscedastic Aleatoric Uncertainty Modeling—0
Towards Robust Object Detection: Identifying and Removing Backdoors via Module Inconsistency Analysis—0
Dropout Sampling for Robust Object Detection in Open-Set Conditions—0
Efficient Event-Based Object Detection: A Hybrid Neural Network with Spatial and Temporal Attention—0
Evaluating the Adversarial Robustness of Detection Transformers—0
Robust Object Detection with Multi-input Multi-output Faster R-CNN—0
SAM2Auto: Auto Annotation Using FLASH—0
Scene-aware Learning Network for Radar Object Detection—0
FMG-Det: Foundation Model Guided Robust Object Detection—0
FROD: Robust Object Detection for Free—0
A Fully Spiking Hybrid Neural Network for Energy-Efficient Object Detection—0
Fusion of an Ensemble of Augmented Image Detectors for Robust Object Detection—0
SDNIA-YOLO: A Robust Object Detection Model for Extreme Weather Conditions—0
High Dynamic Range Modulo Imaging for Robust Object Detection in Autonomous Driving—0
Segmentation is All You Need—0
On the Importance of Backbone to the Adversarial Robustness of Object DetectorsCode0
Soft Sampling for Robust Object DetectionCode0
DyRA: Portable Dynamic Resolution Adjustment Network for Existing DetectorsCode0
Mind the Backbone: Minimizing Backbone Distortion for Robust Object DetectionCode0
DPDETR: Decoupled Position Detection Transformer for Infrared-Visible Object DetectionCode0
Iterative Normalization: Beyond Standardization towards Efficient WhiteningCode0
Switchable Whitening for Deep Representation LearningCode0
Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is ComingCode0
A Robust Learning Approach to Domain Adaptive Object DetectionCode0
ConstScene: Dataset and Model for Advancing Robust Semantic Segmentation in Construction EnvironmentsCode0
Delving into Robust Object Detection from Unmanned Aerial Vehicles: A Deep Nuisance Disentanglement ApproachCode0
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