https://github.com/yfreedomliTHU/mos-pytorch1.1
Breaking the Softmax Bottleneck: A High-Rank RNN Language Model
Papers with Code 아카이브
Vocal Bursts Intensity Prediction
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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/yizhiwang96/deepvecfont_homepage
DeepVecFont: Synthesizing High-quality Vector Fonts via Dual-modality Learning
https://github.com/ypeleg/nfnets-keras
High-Performance Large-Scale Image Recognition Without Normalization
https://github.com/yuanlonghao/T3C_tensor_completion
High-dimension Tensor Completion via Gradient-based Optimization Under Tensor-train Format
https://github.com/yuanyuan-yuan/neural-coverage
Large Scale GAN Training for High Fidelity Natural Image Synthesis
https://github.com/yuanyuanli85/tf-hrnet
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/yukichou/PET
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/yumaloop/CV_report2019
https://github.com/zackzhao1/BackgroundMattingV2-paddle
https://github.com/zbwxp/NRD_decoder
Dynamic Neural Representational Decoders for High-Resolution Semantic Segmentation
https://github.com/zdk123/SpiecEasi
Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models
https://github.com/zgctroy/layoutdiffusion
High-Resolution Image Synthesis with Latent Diffusion Models
https://github.com/zh320/realtime-semantic-segmentation-pytorch
ICNet for Real-Time Semantic Segmentation on High-Resolution Images
https://github.com/zhangyaoyuan/GAN-Simplification
Breaking the Softmax Bottleneck: A High-Rank RNN Language Model
https://github.com/zhengchang467/stiphr
STRPM: A Spatiotemporal Residual Predictive Model for High-Resolution Video Prediction
https://github.com/zhuhel/Parameterized-DNN
https://github.com/zi-w/Ensemble-Bayesian-Optimization
Batched Large-scale Bayesian Optimization in High-dimensional Spaces
https://github.com/zimka/lite_hrnet_tfk
https://github.com/zisianw/FaceBoxes.PyTorch
https://github.com/zl827154659/cc_net
CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data
https://github.com/zqhwzd/CRA
Contextual Residual Aggregation for Ultra High-Resolution Image Inpainting
https://github.com/zyddnys/manga-image-translator
Aggregated Contextual Transformations for High-Resolution Image Inpainting
https://gitlab.com/birder/birder
High-Performance Large-Scale Image Recognition Without Normalization
https://gitlab.com/m.reza.rezaei72/dynamical_deep_neuron
Deep Direct Discriminative Decoders for High-dimensional Time-series Data Analysis
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.