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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://bitbucket.org/columbiadvmm/cdc
공식 코드https://bitbucket.org/dmoltisanti/action_recognition_single_timestamps
공식 코드Action Recognition from Single Timestamp Supervision in Untrimmed Videos
https://bitbucket.org/siddiquemu/usc_mots
공식 코드Unsupervised Spatio-temporal Latent Feature Clustering for Multiple-object Tracking and Segmentation
https://github.com/0liliulei/mask-vos
공식 코드Unified Mask Embedding and Correspondence Learning for Self-Supervised Video Segmentation
https://github.com/11maxed11/phase-based-action-recognition
공식 코드https://github.com/16lemoing/ccvs
공식 코드https://github.com/17Skye17/VideoLT
공식 코드https://github.com/18445864529/mavin
공식 코드MAVIN: Multi-Action Video Generation with Diffusion Models via Transition Video Infilling
https://github.com/1999Lyd/KVTP
공식 코드https://github.com/1Konny/HierarchicalVideoPrediction
공식 코드Revisiting Hierarchical Approach for Persistent Long-Term Video Prediction
https://github.com/1adrianb/video-transformers
공식 코드https://github.com/1xbq1/a2mc
공식 코드Attack-Augmentation Mixing-Contrastive Skeletal Representation Learning
https://github.com/1xbq1/psp-learning
공식 코드Pyramid Self-attention Polymerization Learning for Semi-supervised Skeleton-based Action Recognition
https://github.com/2000222/skateboard-ai
공식 코드SkateboardAI: The Coolest Video Action Recognition for Skateboarding
https://github.com/2313595986/prostatetrus
공식 코드https://github.com/360cvgroup/qihoo-t2x
공식 코드Qihoo-T2X: An Efficient Proxy-Tokenized Diffusion Transformer for Text-to-Any-Task
https://github.com/3dlg-hcvc/OPD
공식 코드https://github.com/3dperceptionlab/visual-wetlandbirds
공식 코드Visual WetlandBirds Dataset: Bird Species Identification and Behavior Recognition in Videos
https://github.com/3huo/3DV-Action
공식 코드https://github.com/3huo/MVDI
공식 코드Action Recognition for Depth Video using Multi-view Dynamic Images
https://github.com/4paradigm-cv/se-stad
공식 코드A Simple and Efficient Pipeline to Build an End-to-End Spatial-Temporal Action Detector
https://github.com/594422814/ContrastCorr
공식 코드Contrastive Transformation for Self-supervised Correspondence Learning
https://github.com/594422814/TransformerTrack
공식 코드Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual Tracking
https://github.com/705062791/pgbig
공식 코드https://github.com/983632847/sam-for-videos
공식 코드https://github.com/99eren99/dirfiaf
공식 코드https://github.com/99eren99/dis25k
공식 코드https://github.com/ABi-dot/Kedkg
공식 코드Knowledge Editing with Dynamic Knowledge Graphs for Multi-Hop Question Answering
https://github.com/AICPS/roadscene2vec
공식 코드roadscene2vec: A Tool for Extracting and Embedding Road Scene-Graphs
https://github.com/AIGeeksGroup/PresentAgent
공식 코드PresentAgent: Multimodal Agent for Presentation Video Generation
https://github.com/AILab-CVC/FreeNoise
공식 코드FreeNoise: Tuning-Free Longer Video Diffusion via Noise Rescheduling
https://github.com/AIS-Bonn/FreqNet
공식 코드https://github.com/AIS-Bonn/LocDepVideoPrediction
공식 코드https://github.com/AIS-Bonn/Local_Freq_Transformer_Net
공식 코드Local Frequency Domain Transformer Networks for Video Prediction
https://github.com/AIS-Bonn/MSPred
공식 코드MSPred: Video Prediction at Multiple Spatio-Temporal Scales with Hierarchical Recurrent Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.