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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
Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving—0
Multimodal Object Detection using Depth and Image Data for Manufacturing Parts—0
UAV3D: A Large-scale 3D Perception Benchmark for Unmanned Aerial Vehicles—0
Towards Robust Object Detection: Identifying and Removing Backdoors via Module Inconsistency Analysis—0
DPDETR: Decoupled Position Detection Transformer for Infrared-Visible Object DetectionCode0
SDNIA-YOLO: A Robust Object Detection Model for Extreme Weather Conditions—0
ConstScene: Dataset and Model for Advancing Robust Semantic Segmentation in Construction EnvironmentsCode0
SimMining-3D: Altitude-Aware 3D Object Detection in Complex Mining Environments: A Novel Dataset and ROS-Based Automatic Annotation Pipeline—0
DyRA: Portable Dynamic Resolution Adjustment Network for Existing DetectorsCode0
FROD: Robust Object Detection for Free—0
Uncertainty-Encoded Multi-Modal Fusion for Robust Object Detection in Autonomous Driving—0
Multi-Task Cross-Modality Attention-Fusion for 2D Object Detection—0
SRCD: Semantic Reasoning with Compound Domains for Single-Domain Generalized Object Detection—0
SF-FSDA: Source-Free Few-Shot Domain Adaptive Object Detection with Efficient Labeled Data Factory—0
On the Importance of Backbone to the Adversarial Robustness of Object DetectorsCode0
Mind the Backbone: Minimizing Backbone Distortion for Robust Object DetectionCode0
A Semantic Consistency Feature Alignment Object Detection Model Based on Mixed-Class Distribution Metrics—0
Weakly Aligned Feature Fusion for Multimodal Object Detection—0
RestoreX-AI: A Contrastive Approach towards Guiding Image Restoration via Explainable AI Systems—0
Robust Object Detection with Multi-input Multi-output Faster R-CNN—0
Towards Robust Object Detection: Bayesian RetinaNet for Homoscedastic Aleatoric Uncertainty Modeling—0
Scene-aware Learning Network for Radar Object Detection—0
A Fully Spiking Hybrid Neural Network for Energy-Efficient Object Detection—0
Multi-Target Domain Adaptation via Unsupervised Domain Classification for Weather Invariant Object Detection—0
Labels Are Not Perfect: Improving Probabilistic Object Detection via Label Uncertainty—0
Exploring Thermal Images for Object Detection in Underexposure Regions for Autonomous Driving—0
Robust Object Detection under Occlusion with Context-Aware CompositionalNets—0
Proposal Learning for Semi-Supervised Object Detection—0
Delving into Robust Object Detection from Unmanned Aerial Vehicles: A Deep Nuisance Disentanglement ApproachCode0
Towards Adversarially Robust Object Detection—0
Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is ComingCode0
Segmentation is All You Need—0
Switchable Whitening for Deep Representation LearningCode0
Iterative Normalization: Beyond Standardization towards Efficient WhiteningCode0
A Robust Learning Approach to Domain Adaptive Object DetectionCode0
Incremental Deep Learning for Robust Object Detection in Unknown Cluttered Environments—0
Soft Sampling for Robust Object DetectionCode0
Fusion of an Ensemble of Augmented Image Detectors for Robust Object Detection—0
Dropout Sampling for Robust Object Detection in Open-Set Conditions—0
Modelling Observation Correlations for Active Exploration and Robust Object Detection—0
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