Papers with Code 아카이브

Video Segmentation

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/kmaninis/OSVOS-PyTorch

One-Shot Video Object Segmentation

https://github.com/kmaninis/OSVOS-caffe

One-Shot Video Object Segmentation

https://github.com/kuangzijian/Flow-Based-Video-Matting

Flow-based Video Segmentation for Human Head and Shoulders

https://github.com/louisfinner/him2sam

SAM 2: Segment Anything in Images and Videos

https://github.com/lxx1991/VS-ReID

Video Object Segmentation with Re-identification

https://github.com/mayu-ot/rethinking-evs

Rethinking the Evaluation of Video Summaries

https://github.com/mindspore-courses/External-Attention-MindSpore/blob/main/model/attention/CrissCrossAttention.py

CCNet: Criss-Cross Attention for Semantic Segmentation

https://github.com/nihalsid/mask2former

Mask2Former for Video Instance Segmentation

https://github.com/oladeha2/shot_boudary_detector

Ridiculously Fast Shot Boundary Detection with Fully Convolutional Neural Networks

https://github.com/omkar13/MaskTrack

Video Object Segmentation with Re-identification

https://github.com/open-mmlab/mmdetection

Mask2Former for Video Instance Segmentation

https://github.com/open-mmlab/mmsegmentation

CCNet: Criss-Cross Attention for Semantic Segmentation

https://github.com/pwc-1/Paper-5/tree/main/mask2former

Mask2Former for Video Instance Segmentation

https://github.com/sajjad-sh33/yolo_sam2

Self-Prompting Polyp Segmentation in Colonoscopy using Hybrid Yolo-SAM 2 Model

https://github.com/scaelles/OSVOS-TensorFlow

One-Shot Video Object Segmentation

https://github.com/shallwe999/TransNetV2-SBD-Visualize

TransNet: A deep network for fast detection of common shot transitions

https://github.com/shashankvkt/video_object_segmentation

YouTube-VOS: Sequence-to-Sequence Video Object Segmentation

https://github.com/simonzeng7108/video-transunet

Video-SwinUNet: Spatio-temporal Deep Learning Framework for VFSS Instance Segmentation

https://github.com/soCzech/MasterThesis

TransNet V2: An effective deep network architecture for fast shot transition detection

https://github.com/soccernet/sn-grounding

SoccerNet-v2: A Dataset and Benchmarks for Holistic Understanding of Broadcast Soccer Videos

https://github.com/soccernet/sn-spotting

SoccerNet-v2: A Dataset and Benchmarks for Holistic Understanding of Broadcast Soccer Videos

https://github.com/theostoican/Guided-Research/blob/main/finetuning_odin_resnet.ipynb

Object discovery and representation networks

https://github.com/wqliu657/TransNetV2

Large-scale, Fast and Accurate Shot Boundary Detection through Spatio-temporal Convolutional Neural Networks

https://github.com/xiuyu0000/new_papers_codes/tree/main/OSVOS

One-Shot Video Object Segmentation

https://github.com/xmed-lab/cardiacnet

GraphEcho: Graph-Driven Unsupervised Domain Adaptation for Echocardiogram Video Segmentation

https://github.com/xmed-lab/m3-uda

GraphEcho: Graph-Driven Unsupervised Domain Adaptation for Echocardiogram Video Segmentation

https://github.com/xujxyang/opentrans

Global Knowledge Calibration for Fast Open-Vocabulary Segmentation

https://github.com/yangchris11/samurai

SAM 2: Segment Anything in Images and Videos

https://github.com/yangyucheng000/University/tree/main/model-3/sam

Underwater Camouflaged Object Tracking Meets Vision-Language SAM2

https://github.com/yformer/EfficientSAM

Efficient Track Anything

https://github.com/zhang-tao-whu/DVIS

DVIS-DAQ: Improving Video Segmentation via Dynamic Anchor Queries

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.