Papers with Code 아카이브
Video Object Detection
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Video object detection is the task of detecting objects from a video as opposed to images.
<span style="color:grey; opacity: 0.6">( Image credit: Learning Motion Priors for Efficient Video Object Detection )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/HYjhkoh/TM_VOD
공식 코드Joint Representation of Temporal Image Sequences and Object Motion for Video Object Detection
https://github.com/JeffCHEN2017/WSSTG
공식 코드Weakly-Supervised Spatio-Temporally Grounding Natural Sentence in Video
https://github.com/MIT-HAN-LAB/temporal-shift-module
공식 코드TSM: Temporal Shift Module for Efficient Video Understanding
https://github.com/NVlabs/wetectron
공식 코드Instance-aware, Context-focused, and Memory-efficient Weakly Supervised Object Detection
https://github.com/Qualcomm-AI-research/delta-distillation
공식 코드https://github.com/RalphMao/PatchNet
공식 코드PatchNet -- Short-range Template Matching for Efficient Video Processing
https://github.com/RalphMao/VMetrics
공식 코드A Delay Metric for Video Object Detection: What Average Precision Fails to Tell
https://github.com/SJTU-LuHe/TransVOD
공식 코드End-to-End Video Object Detection with Spatial-Temporal Transformers
https://github.com/Scalsol/mega.pytorch
공식 코드Memory Enhanced Global-Local Aggregation for Video Object Detection
https://github.com/StarsThu2016/ApproxDet
공식 코드ApproxDet: Content and Contention-Aware Approximate Object Detection for Mobiles
https://github.com/VisDrone/VisDrone-Dataset
공식 코드https://github.com/WISION-Lab/eventful-transformer
공식 코드Eventful Transformers: Leveraging Temporal Redundancy in Vision Transformers
https://github.com/YeLyuUT/VOSDetectron
공식 코드Plug & Play Convolutional Regression Tracker for Video Object Detection
https://github.com/areuther/ai-accelerators
공식 코드https://github.com/bingqingzhang/odd-vod
공식 코드https://github.com/bladewaltz1/clipvid
공식 코드https://github.com/bomps4/multi_resolution_rescored_bytetrack
공식 코드Multi-resolution Rescored ByteTrack for Video Object Detection on Ultra-low-power Embedded Systems
https://github.com/facebookresearch/dino
공식 코드https://github.com/fanq15/FewX
공식 코드https://github.com/giddyyupp/coco-minitrain
공식 코드HoughNet: Integrating near and long-range evidence for visual detection
https://github.com/goodproj13/tf-blender
공식 코드TF-Blender: Temporal Feature Blender for Video Object Detection
https://github.com/guanxiongsun/stpn
공식 코드Spatio-temporal Prompting Network for Robust Video Feature Extraction
https://github.com/guanxiongsun/vfe.pytorch
공식 코드MAMBA: Multi-level Aggregation via Memory Bank for Video Object Detection
https://github.com/hon-wong/ptseformer
공식 코드PTSEFormer: Progressive Temporal-Spatial Enhanced TransFormer Towards Video Object Detection
https://github.com/hu64/RN-VID
공식 코드https://github.com/hu64/ffavod
공식 코드FFAVOD: Feature Fusion Architecture for Video Object Detection
https://github.com/hustvl/LSFA
공식 코드Real-Time and Accurate Object Detection in Compressed Video by Long Short-term Feature Aggregation
https://github.com/jiangzhengkai/LSTS
공식 코드Learning Where to Focus for Efficient Video Object Detection
https://github.com/jiaweihe1996/ba-det
공식 코드3D Video Object Detection with Learnable Object-Centric Global Optimization
https://github.com/juliantrue/movex
공식 코드https://github.com/khurramHashmi/FeatEnHancer
공식 코드FeatEnHancer: Enhancing Hierarchical Features for Object Detection and Beyond Under Low-Light Vision
https://github.com/l-kid/video-object-detection-by-location-anticipation
공식 코드Objects do not disappear: Video object detection by single-frame object location anticipation
https://github.com/manjahdani/csbad
공식 코드Camera clustering for scalable stream-based active distillation
https://github.com/marioduran/tyolov5
공식 코드https://github.com/msracver/Flow-Guided-Feature-Aggregation
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.