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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/KUIS-AI-Tekalp-Research-Group/video-compression
공식 코드End-to-End Rate-Distortion Optimized Learned Hierarchical Bi-Directional Video Compression
https://github.com/KUIS-AI-Tekalp-Research-Group/video-compression/tree/master/Flex-Rate-Hier-Bidir-Video-Compression
공식 코드https://github.com/KaiyangZhou/vsumm-reinforce
공식 코드https://github.com/KaiyuYue/cgnl-network.pytorch
공식 코드https://github.com/KaiyueSun98/T2V-CompBench
공식 코드T2V-CompBench: A Comprehensive Benchmark for Compositional Text-to-video Generation
https://github.com/Kalana304/KORSAL
공식 코드KORSAL: Key-point Detection based Online Real-Time Spatio-Temporal Action Localization
https://github.com/Kay1794/Motion-Graph-Video-Prediction
공식 코드Motion Graph Unleashed: A Novel Approach to Video Prediction
https://github.com/KevinDuarte/CapsuleVOS
공식 코드CapsuleVOS: Semi-Supervised Video Object Segmentation Using Capsule Routing
https://github.com/Khrylx/DLow
공식 코드DLow: Diversifying Latent Flows for Diverse Human Motion Prediction
https://github.com/KimManjin/RSA
공식 코드Relational Self-Attention: What's Missing in Attention for Video Understanding
https://github.com/KwaiVGI/I2V-Adapter
공식 코드I2V-Adapter: A General Image-to-Video Adapter for Diffusion Models
https://github.com/KwaiVGI/LivePortrait
공식 코드LivePortrait: Efficient Portrait Animation with Stitching and Retargeting Control
https://github.com/L-KID/Full-Video-Action-Recognition
공식 코드https://github.com/L-YeZhu/Video-Description-via-Dialog-Agents-ECCV2020
공식 코드Describing Unseen Videos via Multi-Modal Cooperative Dialog Agents
https://github.com/LPMP/LPMP
공식 코드Making Higher Order MOT Scalable: An Efficient Approximate Solver for Lifted Disjoint Paths
https://github.com/LanglandsLin/MS2L
공식 코드MS$^2$L: Multi-Task Self-Supervised Learning for Skeleton Based Action Recognition
https://github.com/LargeWorldModel/LWM
공식 코드World Model on Million-Length Video And Language With Blockwise RingAttention
https://github.com/LeYangNwpu/A2Net
공식 코드Revisiting Anchor Mechanisms for Temporal Action Localization
https://github.com/LeiWangR/HDG
공식 코드A Comparative Review of Recent Kinect-based Action Recognition Algorithms
https://github.com/LeiWangR/LSFNet
공식 코드Loss Switching Fusion with Similarity Search for Video Classification
https://github.com/Levigty/CMCS
공식 코드Cross-Model Cross-Stream Learning for Self-Supervised Human Action Recognition
https://github.com/Lightricks/LTX-Video
공식 코드https://github.com/LingyiHongfd/LVOS
공식 코드https://github.com/Little-Podi/AiATrack
공식 코드AiATrack: Attention in Attention for Transformer Visual Tracking
https://github.com/Liusifei/UVC
공식 코드Joint-task Self-supervised Learning for Temporal Correspondence
https://github.com/LongguangWang/SOF-VSR
공식 코드Deep Video Super-Resolution using HR Optical Flow Estimation
https://github.com/LongguangWang/SOF-VSR-Super-Resolving-Optical-Flow-for-Video-Super-Resolution-
공식 코드Learning for Video Super-Resolution through HR Optical Flow Estimation
https://github.com/LukasHedegaard/co3d
공식 코드Continual 3D Convolutional Neural Networks for Real-time Processing of Videos
https://github.com/Luoyadan/MM2020_ABG
공식 코드Adversarial Bipartite Graph Learning for Video Domain Adaptation
https://github.com/Lyz1213/BadEdit
공식 코드https://github.com/M-Elfeki/Multi-DPP
공식 코드https://github.com/MCG-NJU/AWT
공식 코드AWT: Transferring Vision-Language Models via Augmentation, Weighting, and Transportation
https://github.com/MCG-NJU/CPD-Video
공식 코드Learning Spatiotemporal Features via Video and Text Pair Discrimination
https://github.com/MCG-NJU/MOTIP
공식 코드https://github.com/MCG-NJU/MixFormer
공식 코드MixFormer: End-to-End Tracking with Iterative Mixed Attention
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.