https://github.com/borisdayma/clip-jax
Learning Transferable Visual Models From Natural Language Supervision
Papers with Code 아카이브
Activity Recognition
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 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/bornabr/CAPC
Context-Aware Predictive Coding: A Representation Learning Framework for WiFi Sensing
https://github.com/bornfly-detachment/asymmetric_magvitv2
Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation
https://github.com/boseaslcohort/youtube-8m
https://github.com/bowu/GraphSearch
https://github.com/brandontrabucco/cider
https://github.com/brendanmallery9/entropic-barycenters
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/bruceyo/MMNet
https://github.com/bruceyo/TSMF
https://github.com/bruthyu/bpt-vlm
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/bryanyzhu/two-stream-pytorch
https://github.com/bstadie/third_person_im
Benchmarking Deep Reinforcement Learning for Continuous Control
https://github.com/bt77/pointnet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/buiquangmanhhp1999/age_gender_estimation
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/buriedms/3D-ResNets-Paddle
Can Spatiotemporal 3D CNNs Retrace the History of 2D CNNs and ImageNet?
https://github.com/buyeah1109/KEN
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/buyeah1109/finc
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/cai-jianfeng/ACTOR_mindspore
Action-Conditioned 3D Human Motion Synthesis with Transformer VAE
https://github.com/calciver/Graph-Attention-Networks
https://github.com/camma-public/mcit-ig
Data Splits and Metrics for Method Benchmarking on Surgical Action Triplet Datasets
https://github.com/camma-public/rendezvous
Recognition of Instrument-Tissue Interactions in Endoscopic Videos via Action Triplets
https://github.com/camma-public/ssg-qa
https://github.com/camma-public/ssg-vqa
https://github.com/canturan10/satellighte
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/captaindario/dakanji-single-kanji-recognition
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/carVaba/video-classification-3d-cnn-pytorch
Can Spatiotemporal 3D CNNs Retrace the History of 2D CNNs and ImageNet?
https://github.com/carpedkm/G_TAD_customizing
BSN: Boundary Sensitive Network for Temporal Action Proposal Generation
https://github.com/caspillaga/Conv3DSelfAttention
The "something something" video database for learning and evaluating visual common sense
https://github.com/catalyst-team/gan
https://github.com/cathywu/rllab-multiagent
Benchmarking Deep Reinforcement Learning for Continuous Control
https://github.com/cbfinn/maml_rl
Benchmarking Deep Reinforcement Learning for Continuous Control
https://github.com/cea-list/sce
Similarity Contrastive Estimation for Image and Video Soft Contrastive Self-Supervised Learning
https://github.com/ceezh/llovi
https://github.com/cgebbe/kaggle_pku-autonomous-driving
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/chaitanyadwivedii/3D-Attention-is-All-You-Need
https://github.com/changliu816/CV-paper-review
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.