https://github.com/ganwanshui/simpleoccupancy
공식 코드A Simple Framework for 3D Occupancy Estimation in Autonomous Driving
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A Simple Framework for 3D Occupancy Estimation in Autonomous Driving
End-to-End Object Detection with Adaptive Clustering Transformer
PS-TTL: Prototype-based Soft-labels and Test-Time Learning for Few-shot Object Detection
HGSFusion: Radar-Camera Fusion with Hybrid Generation and Synchronization for 3D Object Detection
M3D-RPN: Monocular 3D Region Proposal Network for Object Detection
GDIP: Gated Differentiable Image Processing for Object-Detection in Adverse Conditions
Multi-Task Learning with Multi-Annotation Triplet Loss for Improved Object Detection
MagicEye: An Intelligent Wearable Towards Independent Living of Visually Impaired
A Robotic Approach towards Quantifying Epipelagic Bound Plastic Using Deep Visual Models
Semi-supervised Object Detection via Virtual Category Learning
Masked Autoencoder for Self-Supervised Pre-training on Lidar Point Clouds
CLAMP-ViT: Contrastive Data-Free Learning for Adaptive Post-Training Quantization of ViTs
Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning
Deep Gradient Learning for Efficient Camouflaged Object Detection
Fast Camouflaged Object Detection via Edge-based Reversible Re-calibration Network
Class-aware Sounding Objects Localization via Audiovisual Correspondence
Hit-Detector: Hierarchical Trinity Architecture Search for Object Detection
Towards Flexible 3D Perception: Object-Centric Occupancy Completion Augments 3D Object Detection
pLitterStreet: Street Level Plastic Litter Detection and Mapping
Attend Refine Repeat: Active Box Proposal Generation via In-Out Localization
LocNet: Improving Localization Accuracy for Object Detection
Object detection via a multi-region & semantic segmentation-aware CNN model
HoughNet: Integrating near and long-range evidence for bottom-up object detection
Hyperspectral Image Dataset for Benchmarking on Salient Object Detection
Parallel Detection for Efficient Video Analytics at the Edge
TOG: Targeted Adversarial Objectness Gradient Attacks on Real-time Object Detection Systems
Exploring Model Learning Heterogeneity for Boosting Ensemble Robustness
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.