https://github.com/merlresearch/TI2V-Zero
공식 코드TI2V-Zero: Zero-Shot Image Conditioning for Text-to-Video Diffusion Models
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/metrics-lab/st-fmri
공식 코드Improving Phenotype Prediction using Long-Range Spatio-Temporal Dynamics of Functional Connectivity
https://github.com/metro-smiles/ProgGen
공식 코드https://github.com/mettyz/ssvc
공식 코드https://github.com/mever-team/ausil
공식 코드Audio-based Near-Duplicate Video Retrieval with Audio Similarity Learning
https://github.com/mever-team/distill-and-select
공식 코드DnS: Distill-and-Select for Efficient and Accurate Video Indexing and Retrieval
https://github.com/mezzelfo/MotionCraft
공식 코드https://github.com/mfaisal59/EpONet
공식 코드EpO-Net: Exploiting Geometric Constraints on Dense Trajectories for Motion Saliency
https://github.com/mfurkanilaslan/vg-tvp
공식 코드VG-TVP: Multimodal Procedural Planning via Visually Grounded Text-Video Prompting
https://github.com/mgiant/2p-gcn
공식 코드Two-person Graph Convolutional Network for Skeleton-based Human Interaction Recognition
https://github.com/mhnasseri/for_tracking
공식 코드https://github.com/mhnasseri/sort_oh
공식 코드Simple online and real-time tracking with occlusion handling
https://github.com/michi-3000/fundus2video
공식 코드https://github.com/michigan-traffic-lab/DECODE
공식 코드DECODE: Domain-aware Continual Domain Expansion for Motion Prediction
https://github.com/michigannlp/vlog_action_localization
공식 코드When Did It Happen? Duration-informed Temporal Localization of Narrated Actions in Vlogs
https://github.com/microsoft/CtP
공식 코드Unsupervised Visual Representation Learning by Tracking Patches in Video
https://github.com/microsoft/SGN
공식 코드Semantics-Guided Neural Networks for Efficient Skeleton-Based Human Action Recognition
https://github.com/microsoft/Swin-Transformer
공식 코드https://github.com/microsoft/UniVL
공식 코드UniVL: A Unified Video and Language Pre-Training Model for Multimodal Understanding and Generation
https://github.com/microsoft/VideoX/tree/master/X-CLIP
공식 코드Expanding Language-Image Pretrained Models for General Video Recognition
https://github.com/microsoft/View-Adaptive-Neural-Networks-for-Skeleton-based-Human-Action-Recognition
공식 코드https://github.com/microsoft/dcvc
공식 코드Hybrid Spatial-Temporal Entropy Modelling for Neural Video Compression
https://github.com/microsoft/lavender
공식 코드LAVENDER: Unifying Video-Language Understanding as Masked Language Modeling
https://github.com/microsoft/nuwa
공식 코드NUWA-Infinity: Autoregressive over Autoregressive Generation for Infinite Visual Synthesis
https://github.com/microsoft/p.910
공식 코드https://github.com/microsoft/peekaboo
공식 코드https://github.com/microsoft/reducio-vae
공식 코드https://github.com/microsoft/swinbert
공식 코드SwinBERT: End-to-End Transformers with Sparse Attention for Video Captioning
https://github.com/microsoft/tensorwatch
공식 코드A System for Real-Time Interactive Analysis of Deep Learning Training
https://github.com/microsoft/transductive-vos.pytorch
공식 코드https://github.com/microsoft/vcd
공식 코드https://github.com/microsoft/videox
공식 코드Expanding Language-Image Pretrained Models for General Video Recognition
https://github.com/microsoft/vidtok
공식 코드https://github.com/microsoft/vsr-challenge
공식 코드ICME 2025 Grand Challenge on Video Super-Resolution for Video Conferencing
https://github.com/microsoft/xpretrain
공식 코드Advancing High-Resolution Video-Language Representation with Large-Scale Video Transcriptions
https://github.com/midas-research/linguistically-informed-frame-interpolation
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.