https://github.com/amohant4/OctConv
Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution
Papers with Code 아카이브
Action Classification
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Image source: The Kinetics Human Action Video Dataset
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ariG23498/TokenLearner
TokenLearner: What Can 8 Learned Tokens Do for Images and Videos?
https://github.com/arunos728/MotionSqueeze
MotionSqueeze: Neural Motion Feature Learning for Video Understanding
https://github.com/arunos728/arunos728.github.io
MotionSqueeze: Neural Motion Feature Learning for Video Understanding
https://github.com/avinashpaul2012/neophyte
High Quality Monocular Depth Estimation via Transfer Learning
https://github.com/ayushrox/TSN_Colab
https://github.com/bespontaneous/ffn
TSM: Temporal Shift Module for Efficient Video Understanding
https://github.com/bespontaneous/mca-pytorch
TSM: Temporal Shift Module for Efficient Video Understanding
https://github.com/braincreators/octconv
Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution
https://github.com/brandon-wu76/monocular-depth-estimation
High Quality Monocular Depth Estimation via Transfer Learning
https://github.com/bruceyo/MMNet
https://github.com/ceezh/llovi
https://github.com/chaitanyadwivedii/3D-Attention-is-All-You-Need
https://github.com/changliu816/CV-paper-review
https://github.com/chaoyuaw/pytorch-coviar
https://github.com/chenhsing/svformer
https://github.com/chunfeng0301/Flow
https://github.com/cioppaanthony/context-aware-loss
SoccerNet: A Scalable Dataset for Action Spotting in Soccer Videos
https://github.com/cmsflash/efficient-attention
https://github.com/code-implementation1/Code1/tree/main/ecolite
ECO: Efficient Convolutional Network for Online Video Understanding
https://github.com/code-implementation1/Code2/tree/main/AdderNGD
ECO: Efficient Convolutional Network for Online Video Understanding
https://github.com/code-implementation1/Code6/tree/main/Non_local
https://github.com/code-implementation1/Code7/tree/main/resnet3d
https://github.com/code-implementation1/Code8/tree/main/slowfast
https://github.com/craston/MARS
https://github.com/cyb1212/Monocular-Depth-Estimation-vis-Transfer-learning-Winter-school-
High Quality Monocular Depth Estimation via Transfer Learning
https://github.com/d-li14/octconv.pytorch
Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution
https://github.com/damien911224/theWorldInSafety
Two-Stream Convolutional Networks for Action Recognition in Videos
https://github.com/dancelogue/kinetics-datasets-downloader
https://github.com/daniallin/DenseDepth-Pytorch
High Quality Monocular Depth Estimation via Transfer Learning
https://github.com/daniansan/i3d_mindspore
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
https://github.com/daniel-code/TubeViT
Rethinking Video ViTs: Sparse Video Tubes for Joint Image and Video Learning
https://github.com/darrylho/dejavid
https://github.com/davide-coccomini/TimeSformer-Video-Classification
Is Space-Time Attention All You Need for Video Understanding?
https://github.com/ddddwee1/Octave-Convolution
Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution
https://github.com/deepjyotisaha85/DenseDepth
High Quality Monocular Depth Estimation via Transfer Learning
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.