https://github.com/wangyi111/international-archaeology-ai-challenge
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
Papers with Code 아카이브
Activity Recognition
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- 하위 태스크
- 11
- 평가표
- 4
- 보존된 평가 기록
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Human Activity Recognition is the problem of identifying events performed by humans given a video input. It is formulated as a binary (or multiclass) classification problem of outputting activity class labels. Activity Recognition is an important problem with many societal applications including smart surveillance, video search/retrieval, intelligent robots, and other monitoring systems.
Source: Learning Latent Sub-events in Activity Videos Using Temporal Attention Filters
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/wasilone11/ICPR-RIP-2024
A Closer Look at Spatiotemporal Convolutions for Action Recognition
https://github.com/waynshang/Gesture-Recognition-with-3DCNN
Learning Spatiotemporal Features with 3D Convolutional Networks
https://github.com/weixuan-wang123/ReMaKE
Editing Large Language Models: Problems, Methods, and Opportunities
https://github.com/weiyangfb/PyTorchSparseGAT
https://github.com/wenhuchen/data-to-text-evaluation-metric
https://github.com/whut2962575697/gat_sementic_segmentation
https://github.com/whwu95/Cap4Video
Revisiting Classifier: Transferring Vision-Language Models for Video Recognition
https://github.com/whwu95/GPT4Vis
Revisiting Classifier: Transferring Vision-Language Models for Video Recognition
https://github.com/wikibook/keras
https://github.com/witignite/Frustum-PointNet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/wonderland-dsg/pointnet-grid
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/woodfrog/ActionRecognition
Two-Stream Convolutional Networks for Action Recognition in Videos
https://github.com/woretaw23/cGAN
https://github.com/wufan-tb/gmm_dae
Video Anomaly Detection by Estimating Likelihood of Representations
https://github.com/wuryantoAji/POINTNET
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/wusaifei/HWCC_image_classification
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/wushidonguc/two-stream-action-recognition-keras
UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild
https://github.com/wyndwarrior/imitation_from_observation
Benchmarking Deep Reinforcement Learning for Continuous Control
https://github.com/wzmsltw/BSN-boundary-sensitive-network
BSN: Boundary Sensitive Network for Temporal Action Proposal Generation
https://github.com/xiaogangLi/tensorflow-VTN
Lightweight Network Architecture for Real-Time Action Recognition
https://github.com/xiaoiker/GCN-NAS
Learning Graph Convolutional Network for Skeleton-based Human Action Recognition by Neural Searching
https://github.com/xingchenzhao/Generating-Human-Skeletons-with-Mutual-Actions-WGAN-Pytorch
Human Action Generation with Generative Adversarial Networks
https://github.com/xingchenzhao/deep-learning-team-project
Human Action Generation with Generative Adversarial Networks
https://github.com/xingxingyoulei/infer_cgan_onnx/tree/master/research/cv/CGAN
https://github.com/xiuyu0000/new_papers_codes/tree/main/I3D
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
https://github.com/xiuyu0000/vision/blob/main/mindvision/classification/models/backbones/efficientnet.py
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/xiuyu0000/vision/blob/main/mindvision/ms3d/models/pointnet2cls.py
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/xiuyu0000/vision/blob/main/mindvision/msvideo/models/c3d.py
Learning Spatiotemporal Features with 3D Convolutional Networks
https://github.com/xiuyu0000/vision/blob/main/mindvision/msvideo/models/i3d.py
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
https://github.com/xiuyu0000/vision/blob/main/mindvision/msvideo/models/r2plus1d.py
A Closer Look at Spatiotemporal Convolutions for Action Recognition
https://github.com/xlliu7/BMN-Boundary-Matching-Network
BMN: Boundary-Matching Network for Temporal Action Proposal Generation
https://github.com/xrenaa/Human-Motion-Analysis-with-Deep-Metric-Learning
https://github.com/xslidi/EfficientNets_ddl_apex
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/xurui1217/pointnet.pytorch-master
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/xuxy09/texformer
3D Human Shape and Pose from a Single Low-Resolution Image with Self-Supervised Learning
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.