Papers with Code 아카이브
Vocal Bursts Intensity Prediction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 1
- 보존된 평가 기록
- 2
predict the intensity of 10 categorical emotions
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/kidist-amde/biggan-pytorch
Large Scale GAN Training for High Fidelity Natural Image Synthesis
https://github.com/kingcong/HRNetW48_seg
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/kingcong/RefineNet
RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
https://github.com/kingcong/gpu_HRNetW48_cls
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/kingcong/gpu_RefineNet
RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
https://github.com/kingcong/models/tree/main/lite-hrnet
https://github.com/kmaninis/COB
Convolutional Oriented Boundaries: From Image Segmentation to High-Level Tasks
https://github.com/kmkwon94/ainize-laser
CCMatrix: Mining Billions of High-Quality Parallel Sentences on the WEB
https://github.com/kousun12/TFDE
Solving high-dimensional partial differential equations using deep learning
https://github.com/krystalan/k-sportssum
SportsSum2.0: Generating High-Quality Sports News from Live Text Commentary
https://github.com/kshmawj111/solar_energy_forecast
High-Dimensional Multivariate Forecasting with Low-Rank Gaussian Copula Processes
https://github.com/kukby/Mish-semantic-segmentation-pytorch
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/kultzak/MCLA
Robust Lineage Reconstruction from High-Dimensional Single-Cell Data
https://github.com/l0stpenguin/DenseDepthResNet
High Quality Monocular Depth Estimation via Transfer Learning
https://github.com/labmlai/annotated_deep_learning_paper_implementations
High-Dimensional Continuous Control Using Generalized Advantage Estimation
https://github.com/laowang666888/HRNET
Deep High-Resolution Representation Learning for Human Pose Estimation
https://github.com/leehomyc/Faster-High-Res-Neural-Inpainting
High-Resolution Image Inpainting using Multi-Scale Neural Patch Synthesis
https://github.com/leeyegy/SimDR
Deep High-Resolution Representation Learning for Human Pose Estimation
https://github.com/leeyegy/simcc
Deep High-Resolution Representation Learning for Human Pose Estimation
https://github.com/leftthomas/restormer
Restormer: Efficient Transformer for High-Resolution Image Restoration
https://github.com/leminhbinh0209/add
FaceShifter: Towards High Fidelity And Occlusion Aware Face Swapping
https://github.com/lemon-liley/isabella
High Quality Monocular Depth Estimation via Transfer Learning
https://github.com/leondgarse/keras_cv_attention_models/tree/main/keras_cv_attention_models/gpvit
GPViT: A High Resolution Non-Hierarchical Vision Transformer with Group Propagation
https://github.com/leondgarse/keras_cv_attention_models/tree/main/keras_cv_attention_models/hornet
HorNet: Efficient High-Order Spatial Interactions with Recursive Gated Convolutions
https://github.com/leondgarse/keras_cv_attention_models/tree/main/keras_cv_attention_models/nfnets
High-Performance Large-Scale Image Recognition Without Normalization
https://github.com/leshanbog/lasertagger
https://github.com/lewisluk/BoundaryAwareNetwork
Boundary-Aware Network for Fast and High-Accuracy Portrait Segmentation
https://github.com/lferry007/LargeVis
https://github.com/lilijiangg/autodiffusion
High-Resolution Image Synthesis with Latent Diffusion Models
https://github.com/liminn/icnet-pytorch
ICNet for Real-Time Semantic Segmentation on High-Resolution Images
https://github.com/linlina/mlminf
Statistical significance in high-dimensional linear mixed models
https://github.com/lisilin013/ICNet-tensorflow-ros
ICNet for Real-Time Semantic Segmentation on High-Resolution Images
https://github.com/liuch37/semantic-segmentation
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/liuzhen03/ADNet
Attention-guided Network for Ghost-free High Dynamic Range Imaging
https://github.com/logpai/loglizer
Anomaly Detection using Autoencoders in High Performance Computing Systems
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.