Papers with Code 아카이브
Action Localization
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Action Localization is finding the spatial and temporal co ordinates for an action in a video. An action localization model will identify which frame an action start and ends in video and return the x,y coordinates of an action. Further the co ordinates will change when the object performing action undergoes a displacement.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/sotif-avlab/sind
공식 코드https://github.com/sperimental3/charon
공식 코드Mask and Compress: Efficient Skeleton-based Action Recognition in Continual Learning
https://github.com/srijandas07/VPN
공식 코드VPN: Learning Video-Pose Embedding for Activities of Daily Living
https://github.com/srijandas07/vpnplusplus
공식 코드VPN++: Rethinking Video-Pose embeddings for understanding Activities of Daily Living
https://github.com/ssarfraz/FINCH-CLustering
공식 코드Temporally-Weighted Hierarchical Clustering for Unsupervised Action Segmentation
https://github.com/sscivier/gp-prob-earthquake-shaking
공식 코드Gaussian Processes for Probabilistic Estimates of Earthquake Ground Shaking: A 1-D Proof-of-Concept
https://github.com/sshaoshuai/mtr
공식 코드MTR-A: 1st Place Solution for 2022 Waymo Open Dataset Challenge -- Motion Prediction
https://github.com/sssste/react
공식 코드https://github.com/stan-hua/temporal_hydronephrosis
공식 코드https://github.com/stanfordnlp/pyvene
공식 코드pyvene: A Library for Understanding and Improving PyTorch Models via Interventions
https://github.com/stepankonev/MotionCNN-Waymo-Open-Motion-Dataset
공식 코드MotionCNN: A Strong Baseline for Motion Prediction in Autonomous Driving
https://github.com/stepankonev/waymo-motion-prediction-chalenge-2022-multipath-plus-plus
공식 코드https://github.com/stergiosbamp/deep-physical-activity-prediction
공식 코드https://github.com/steveliao93/gcn_logsigrnn
공식 코드Logsig-RNN: a novel network for robust and efficient skeleton-based action recognition
https://github.com/sthoduka/handover_failure_detection
공식 코드A Multimodal Handover Failure Detection Dataset and Baselines
https://github.com/stnoah1/infogcn2
공식 코드https://github.com/stnoah1/sode
공식 코드https://github.com/stoa-xh91/acfl
공식 코드Skeleton-based Action Recognition via Adaptive Cross-Form Learning
https://github.com/stoneMo/YOWOv2
공식 코드Towards Improving Spatiotemporal Action Recognition in Videos
https://github.com/stuarteiffert/MCTS-GRNN
공식 코드Path Planning in Dynamic Environments using Generative RNNs and Monte Carlo Tree Search
https://github.com/suakaw/bdq_privacyar
공식 코드Privacy-Preserving Action Recognition via Motion Difference Quantization
https://github.com/sudo-Boris/mr-Blip
공식 코드The Surprising Effectiveness of Multimodal Large Language Models for Video Moment Retrieval
https://github.com/suhaisheng/difsd
공식 코드https://github.com/sujoyp/wtalc-pytorch
공식 코드W-TALC: Weakly-supervised Temporal Activity Localization and Classification
https://github.com/sunzhihao18/ForgerySleuth
공식 코드ForgerySleuth: Empowering Multimodal Large Language Models for Image Manipulation Detection
https://github.com/superz678/mg-had
공식 코드https://github.com/swathikirans/LSTA
공식 코드LSTA: Long Short-Term Attention for Egocentric Action Recognition
https://github.com/swathikirans/gsf
공식 코드https://github.com/swc-17/sparsedrive
공식 코드SparseDrive: End-to-End Autonomous Driving via Sparse Scene Representation
https://github.com/sycny/rae
공식 코드Retrieval-enhanced Knowledge Editing in Language Models for Multi-Hop Question Answering
https://github.com/syon-li/coachhook
공식 코드https://github.com/syscv/trafficbots
공식 코드TrafficBots: Towards World Models for Autonomous Driving Simulation and Motion Prediction
https://github.com/tabguigui/fiptr
공식 코드https://github.com/tailin1009/dualhead-network
공식 코드Learning Multi-Granular Spatio-Temporal Graph Network for Skeleton-based Action Recognition
https://github.com/tal-aurorax/scen
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.