https://github.com/vita-mllm/long-vita
공식 코드Long-VITA: Scaling Large Multi-modal Models to 1 Million Tokens with Leading Short-Context Accuray
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/vitae-transformer/vos-llb
공식 코드https://github.com/vitusbenson/greenearthnet
공식 코드https://github.com/vividle/backtal
공식 코드Background-Click Supervision for Temporal Action Localization
https://github.com/vividle/online-action-detection
공식 코드Structured Attention Composition for Temporal Action Localization
https://github.com/vividle/structured-attention-composition
공식 코드Structured Attention Composition for Temporal Action Localization
https://github.com/vivoCameraResearch/Hyper-Motion
공식 코드HyperMotion: DiT-Based Pose-Guided Human Image Animation of Complex Motions
https://github.com/vkalogeiton/caffe
공식 코드Action Tubelet Detector for Spatio-Temporal Action Localization
https://github.com/vlkeb/vlkeb
공식 코드VLKEB: A Large Vision-Language Model Knowledge Editing Benchmark
https://github.com/void-96/har_tencon2022
공식 코드Handwashing Action Detection System for an Autonomous Social Robot
https://github.com/voletiv/mcvd-pytorch
공식 코드MCVD: Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation
https://github.com/vpx-ecnu/find-website
공식 코드FIND: Fine-tuning Initial Noise Distribution with Policy Optimization for Diffusion Models
https://github.com/vqassessment/bvqi
공식 코드Exploring Opinion-unaware Video Quality Assessment with Semantic Affinity Criterion
https://github.com/vqassessment/dover
공식 코드https://github.com/vqassessment/maxvqa
공식 코드https://github.com/vt-vl-lab/SDN
공식 코드Why Can't I Dance in the Mall? Learning to Mitigate Scene Bias in Action Recognition
https://github.com/vturrisi/udavt
공식 코드Unsupervised Domain Adaptation for Video Transformers in Action Recognition
https://github.com/vujas-eteph/lazyxmem
공식 코드https://github.com/vukasin-stanojevic/BoostTrack
공식 코드BoostTrack++: using tracklet information to detect more objects in multiple object tracking
https://github.com/vut-hfut/micro-action
공식 코드https://github.com/vvarga90/gnn_annot
공식 코드Fast Interactive Video Object Segmentation with Graph Neural Networks
https://github.com/vvhj/tsgcnext
공식 코드https://github.com/vvictoryuki/animatezero
공식 코드AnimateZero: Video Diffusion Models are Zero-Shot Image Animators
https://github.com/vztu/RAPIQUE
공식 코드RAPIQUE: Rapid and Accurate Video Quality Prediction of User Generated Content
https://github.com/w-shuoyan/evenhancer
공식 코드https://github.com/walzimmer/3d-bat
공식 코드https://github.com/wan-video/wan2.1
공식 코드https://github.com/wang-chen/LGL
공식 코드https://github.com/wang-chen/lgl-action-recognition
공식 코드https://github.com/wangbing1416/hami-m3d
공식 코드Harmfully Manipulated Images Matter in Multimodal Misinformation Detection
https://github.com/wangbo-zhao/WSVSOD
공식 코드https://github.com/wangchi95/active-boundary-loss
공식 코드https://github.com/wangheda/youtube-8m
공식 코드The Monkeytyping Solution to the YouTube-8M Video Understanding Challenge
https://github.com/wangjiangshan0725/rf-solver-edit
공식 코드https://github.com/wangjiarui153/AIGV-Assessor
공식 코드https://github.com/wangjk666/omnivid
공식 코드OmniVid: A Generative Framework for Universal Video Understanding
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.