https://github.com/guojiaqi-1020/medivlad
공식 코드Efficient Lung Ultrasound Severity Scoring Using Dedicated Feature Extractor
Papers with Code 아카이브
Video Classification
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
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- 보존된 평가 기록
- 31
Video Classification is the task of producing a label that is relevant to the video given its frames. A good video level classifier is one that not only provides accurate frame labels, but also best describes the entire video given the features and the annotations of the various frames in the video. For example, a video might contain a tree in some frame, but the label that is central to the video might be something else (e.g., “hiking”). The granularity of the labels that are needed to describe the frames and the video depends on the task. Typical tasks include assigning one or more global labels to the video, and assigning one or more labels for each frame inside the video.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/guoxih/Busy-Quiet-Video-Disentangling-for-Video-Classification
공식 코드https://github.com/guoxih/region-based-non-local-network
공식 코드https://github.com/gurkirt/actNet-inAct
공식 코드Untrimmed Video Classification for Activity Detection: submission to ActivityNet Challenge
https://github.com/haoyanbin918/attention-in-attention
공식 코드Attention in Attention: Modeling Context Correlation for Efficient Video Classification
https://github.com/hate-alert/hatemm
공식 코드https://github.com/hazyresearch/state-spaces
공식 코드S4ND: Modeling Images and Videos as Multidimensional Signals Using State Spaces
https://github.com/hesamaraghi/pushing-boundaries-event-subsampling
공식 코드Pushing the boundaries of event subsampling in event-based video classification using CNNs
https://github.com/hoangnguyenm/bridle
공식 코드BRIDLE: Generalized Self-supervised Learning with Quantization
https://github.com/holistic-video-understanding/HVU-Dataset
공식 코드https://github.com/hrx2010/YouTube8m-Text
공식 코드Truly Multi-modal YouTube-8M Video Classification with Video, Audio, and Text
https://github.com/iduta/pyconv
공식 코드Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual Recognition
https://github.com/ispamm/GRAM
공식 코드https://github.com/jampang41/cst-s3d
공식 코드https://github.com/jeffhernandez1995/vic-mae
공식 코드https://github.com/jeunyuli/muaf
공식 코드MUVF-YOLOX: A Multi-modal Ultrasound Video Fusion Network for Renal Tumor Diagnosis
https://github.com/jmalves5/read-my-ears
공식 코드Read My Ears! Horse Ear Movement Detection for Equine Affective State Assessment
https://github.com/josephcao0327/stylefool
공식 코드StyleFool: Fooling Video Classification Systems via Style Transfer
https://github.com/joslefaure/HERMES
공식 코드HERMES: temporal-coHERent long-forM understanding with Episodes and Semantics
https://github.com/kaleab-k/VideoAT
공식 코드Analysis and Extensions of Adversarial Training for Video Classification
https://github.com/karttikeya/minrev
공식 코드https://github.com/kenshohara/3D-ResNets-PyTorch
공식 코드Would Mega-scale Datasets Further Enhance Spatiotemporal 3D CNNs?
https://github.com/kiyoon/channel_sampling
공식 코드Capturing Temporal Information in a Single Frame: Channel Sampling Strategies for Action Recognition
https://github.com/kpeng9510/musclemap
공식 코드https://github.com/labribkb/fem
공식 코드https://github.com/laura-wang/video_repres_mas
공식 코드https://github.com/laurarkart/Physical-Anomalous-Trajectory-or-Motion-PHANTOM-Dataset
공식 코드Approaches Toward Physical and General Video Anomaly Detection
https://github.com/longxiang92/Flash-MNIST
공식 코드Attention Clusters: Purely Attention Based Local Feature Integration for Video Classification
https://github.com/lxhit/STAF
공식 코드MASTAF: A Model-Agnostic Spatio-Temporal Attention Fusion Network for Few-shot Video Classification
https://github.com/martinetoering/ViCC
공식 코드Self-supervised Video Representation Learning with Cross-Stream Prototypical Contrasting
https://github.com/mcg-nju/fsl-video
공식 코드A Closer Look at Few-Shot Video Classification: A New Baseline and Benchmark
https://github.com/md-mohaiminul/ViS4mer
공식 코드Long Movie Clip Classification with State-Space Video Models
https://github.com/md-mohaiminul/trans4mer
공식 코드Efficient Movie Scene Detection using State-Space Transformers
https://github.com/medaitech/u_i2v
공식 코드Ultrasound Image-to-Video Synthesis via Latent Dynamic Diffusion Models
https://github.com/mm4spa/eigd
공식 코드A Unified Taxonomy and Multimodal Dataset for Events in Invasion Games
https://github.com/mrsfgl/MBTTDA
공식 코드Multi-Branch Tensor Network Structure for Tensor-Train Discriminant Analysis
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.