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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/appletea233/llava-st
공식 코드LLaVA-ST: A Multimodal Large Language Model for Fine-Grained Spatial-Temporal Understanding
https://github.com/appletea233/temporal-r1
공식 코드Reinforcement Learning Tuning for VideoLLMs: Reward Design and Data Efficiency
https://github.com/applied-machine-learning-lab/mm4ke
공식 코드https://github.com/araachie/yoda
공식 코드Learn the Force We Can: Enabling Sparse Motion Control in Multi-Object Video Generation
https://github.com/aranciokov/fsmmda_videoretrieval
공식 코드A Feature-space Multimodal Data Augmentation Technique for Text-video Retrieval
https://github.com/aranciokov/ranp
공식 코드Learning video retrieval models with relevance-aware online mining
https://github.com/aranciokov/relevancemargin-icmr22
공식 코드Relevance-based Margin for Contrastively-trained Video Retrieval Models
https://github.com/aras62/vision-based-prediction
공식 코드https://github.com/araujoalexandre/youtube8m-circulant
공식 코드Training compact deep learning models for video classification using circulant matrices
https://github.com/arnab-api/romba
공식 코드https://github.com/aroitberg/sims4action
공식 코드https://github.com/art-jang/sign-to-subtitle
공식 코드Deep Understanding of Sign Language for Sign to Subtitle Alignment
https://github.com/arthur-qiu/FreeNoise-AnimateDiff
공식 코드FreeNoise: Tuning-Free Longer Video Diffusion via Noise Rescheduling
https://github.com/arthur-qiu/freenoise-lavie
공식 코드FreeNoise: Tuning-Free Longer Video Diffusion via Noise Rescheduling
https://github.com/arthur-qiu/freetraj
공식 코드FreeTraj: Tuning-Free Trajectory Control in Video Diffusion Models
https://github.com/arthur-qiu/stylefacev
공식 코드StyleFaceV: Face Video Generation via Decomposing and Recomposing Pretrained StyleGAN3
https://github.com/arturxe2/astra
공식 코드https://github.com/arunbalajeev/query-video-summary
공식 코드Query-adaptive Video Summarization via Quality-aware Relevance Estimation
https://github.com/arunos728/SELFY
공식 코드Learning Self-Similarity in Space and Time as Generalized Motion for Video Action Recognition
https://github.com/arvid-pku/atoke
공식 코드History Matters: Temporal Knowledge Editing in Large Language Model
https://github.com/asankagp/UAV-GESTURE
공식 코드UAV-GESTURE: A Dataset for UAV Control and Gesture Recognition
https://github.com/asankagp/mod20
공식 코드A Multi-viewpoint Outdoor Dataset for Human Action Recognition
https://github.com/asdfo123/scedit
공식 코드https://github.com/asheshjain399/RNNexp
공식 코드https://github.com/asrafulashiq/hamnet
공식 코드A Hybrid Attention Mechanism for Weakly-Supervised Temporal Action Localization
https://github.com/asrafulashiq/wsad
공식 코드Weakly Supervised Temporal Action Localization Using Deep Metric Learning
https://github.com/assembly101/assembly101.github.io
공식 코드Assembly101: A Large-Scale Multi-View Video Dataset for Understanding Procedural Activities
https://github.com/astra-vision/SceneRF
공식 코드SceneRF: Self-Supervised Monocular 3D Scene Reconstruction with Radiance Fields
https://github.com/atelili/2bivqa
공식 코드2BiVQA: Double Bi-LSTM based Video Quality Assessment of UGC Videos
https://github.com/atlas-eccv22/awesome-temporal-action-segmentation
공식 코드Temporal Action Segmentation: An Analysis of Modern Techniques
https://github.com/au-revoir/model-editing-ft
공식 코드https://github.com/autonomousvision/kitti360labeltool
공식 코드KITTI-360: A Novel Dataset and Benchmarks for Urban Scene Understanding in 2D and 3D
https://github.com/autonomousvision/kitti360scripts
공식 코드KITTI-360: A Novel Dataset and Benchmarks for Urban Scene Understanding in 2D and 3D
https://github.com/aviclu/long-context-qa-contrast
공식 코드Long Context Question Answering via Supervised Contrastive Learning
https://github.com/aviclu/seq-contrast-qa
공식 코드Long Context Question Answering via Supervised Contrastive Learning
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