https://github.com/grokcv/hazydet
공식 코드HazyDet: Open-source Benchmark for Drone-view Object Detection with Depth-cues in Hazy Scenes
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HazyDet: Open-source Benchmark for Drone-view Object Detection with Depth-cues in Hazy Scenes
Monocular 3D Object Detection with Sequential Feature Association and Depth Hint Augmentation
Meta Faster R-CNN: Towards Accurate Few-Shot Object Detection with Attentive Feature Alignment
Improved Techniques for Learning to Dehaze and Beyond: A Collective Study
OED: Towards One-stage End-to-End Dynamic Scene Graph Generation
Spatio-temporal Prompting Network for Robust Video Feature Extraction
MAMBA: Multi-level Aggregation via Memory Bank for Video Object Detection
Explain to Fix: A Framework to Interpret and Correct DNN Object Detector Predictions
DNN Feature Map Compression using Learned Representation over GF(2)
Exploring Deeper! Segment Anything Model with Depth Perception for Camouflaged Object Detection
General Geometry-aware Weakly Supervised 3D Object Detection
Voxel Mamba: Group-Free State Space Models for Point Cloud based 3D Object Detection
Text-guided Sparse Voxel Pruning for Efficient 3D Visual Grounding
Domain-Specific Lexical Grounding in Noisy Visual-Textual Documents
Pixel Distillation: A New Knowledge Distillation Scheme for Low-Resolution Image Recognition
3D Copy-Paste: Physically Plausible Object Insertion for Monocular 3D Detection
Beyond Generation: Harnessing Text to Image Models for Object Detection and Segmentation
AFPN: Asymptotic Feature Pyramid Network for Object Detection
Multi Scale Curriculum CNN for Context-Aware Breast MRI Malignancy Classification
Real-Time Accident Detection in Traffic Surveillance Using Deep Learning
Vehicle-Infrastructure Cooperative 3D Object Detection via Feature Flow Prediction
Commonsense Prototype for Outdoor Unsupervised 3D Object Detection
Virtual Sparse Convolution for Multimodal 3D Object Detection
CAGroup3D: Class-Aware Grouping for 3D Object Detection on Point Clouds
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.