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Robust Object Detection
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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;
<span style="color:grey; opacity: 0.6">( Image credit: Benchmarking Robustness in Object Detection )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability
SAM2Auto: Auto Annotation Using FLASH
FMG-Det: Foundation Model Guided Robust Object Detection
VLC Fusion: Vision-Language Conditioned Sensor Fusion for Robust Object Detection
LLM-Empowered Embodied Agent for Memory-Augmented Task Planning in Household Robotics
Learning to Borrow Features for Improved Detection of Small Objects in Single-Shot Detectors
High Dynamic Range Modulo Imaging for Robust Object Detection in Autonomous Driving
WS-DETR: Robust Water Surface Object Detection through Vision-Radar Fusion with Detection Transformer
Robust Object Detection of Underwater Robot based on Domain Generalization
Generalized Diffusion Detector: Mining Robust Features from Diffusion Models for Domain-Generalized Detection
RobuRCDet: Enhancing Robustness of Radar-Camera Fusion in Bird's Eye View for 3D Object Detection
UAV Cognitive Semantic Communications Enabled by Knowledge Graph for Robust Object Detection
Evaluating the Adversarial Robustness of Detection Transformers
PhysAug: A Physical-guided and Frequency-based Data Augmentation for Single-Domain Generalized Object Detection
Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving
Multimodal Object Detection using Depth and Image Data for Manufacturing Parts
UAV3D: A Large-scale 3D Perception Benchmark for Unmanned Aerial Vehicles
Towards Robust Object Detection: Identifying and Removing Backdoors via Module Inconsistency Analysis
RoboSense: Large-scale Dataset and Benchmark for Egocentric Robot Perception and Navigation in Crowded and Unstructured Environments
DPDETR: Decoupled Position Detection Transformer for Infrared-Visible Object Detection
SDNIA-YOLO: A Robust Object Detection Model for Extreme Weather Conditions
SemanticSpray++: A Multimodal Dataset for Autonomous Driving in Wet Surface Conditions
ConstScene: Dataset and Model for Advancing Robust Semantic Segmentation in Construction Environments
Object-Aware Domain Generalization for Object Detection
SimMining-3D: Altitude-Aware 3D Object Detection in Complex Mining Environments: A Novel Dataset and ROS-Based Automatic Annotation Pipeline
Strong but simple: A Baseline for Domain Generalized Dense Perception by CLIP-based Transfer Learning
DyRA: Portable Dynamic Resolution Adjustment Network for Existing Detectors
On the Robustness of Object Detection Models on Aerial Images
Improved Region Proposal Network for Enhanced Few-Shot Object Detection
FROD: Robust Object Detection for Free
Uncertainty-Encoded Multi-Modal Fusion for Robust Object Detection in Autonomous Driving
COCO-O: A Benchmark for Object Detectors under Natural Distribution Shifts
Multi-Task Cross-Modality Attention-Fusion for 2D Object Detection
SRCD: Semantic Reasoning with Compound Domains for Single-Domain Generalized Object Detection
SF-FSDA: Source-Free Few-Shot Domain Adaptive Object Detection with Efficient Labeled Data Factory
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.