https://github.com/StonyBrookNLP/HAQAE
공식 코드Hierarchical Quantized Representations for Script Generation
Papers with Code 아카이브
NLP based Person Retrival
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 1
- 평가표
- 0
- 보존된 평가 기록
- 0
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Storife/RANet
공식 코드RANet: Ranking Attention Network for Fast Video Object Segmentation
https://github.com/Styrke/master-code
공식 코드Neural Machine Translation with Characters and Hierarchical Encoding
https://github.com/SuSir1996/MU-GAN
공식 코드MU-GAN: Facial Attribute Editing based on Multi-attention Mechanism
https://github.com/SunbowLiu/SurfaceFusion
공식 코드Understanding and Improving Encoder Layer Fusion in Sequence-to-Sequence Learning
https://github.com/Sunjuhyeong/SAM_STBAVA
공식 코드Extending Segment Anything Model into Auditory and Temporal Dimensions for Audio-Visual Segmentation
https://github.com/SwordYork/DCNMT
공식 코드https://github.com/THUDM/GLM
공식 코드GLM: General Language Model Pretraining with Autoregressive Blank Infilling
https://github.com/TJUMMG/DS-Net
공식 코드DS-Net: Dynamic Spatiotemporal Network for Video Salient Object Detection
https://github.com/TRI-ML/vidar
공식 코드https://github.com/TTS-Research/PEL-TTS
공식 코드Parameter-Efficient Learning for Text-to-Speech Accent Adaptation
https://github.com/TUM-LMF/FutureGAN
공식 코드https://github.com/TXH-mercury/VALOR
공식 코드VALOR: Vision-Audio-Language Omni-Perception Pretraining Model and Dataset
https://github.com/TashinAhmed/CloudsClassification
공식 코드Classification and understanding of cloud structures via satellite images with EfficientUNet
https://github.com/Taylister/FontFits
공식 코드Font Style that Fits an Image -- Font Generation Based on Image Context
https://github.com/Theerasit/CounterfactualDepth
공식 코드https://github.com/ThiagoCF05/webnlg
공식 코드Neural data-to-text generation: A comparison between pipeline and end-to-end architectures
https://github.com/TiagoCortinhal/SalsaNext
공식 코드https://github.com/TianBaoGe/DS-TransUNet
공식 코드DS-TransUNet:Dual Swin Transformer U-Net for Medical Image Segmentation
https://github.com/Tinysqua/UWAT-GAN
공식 코드https://github.com/TmacMai/ARGF_multimodal_fusion
공식 코드https://github.com/TobeyYang/S2S_Temp
공식 코드https://github.com/Tombs98/CAPTNet
공식 코드Prompt-based Ingredient-Oriented All-in-One Image Restoration
https://github.com/Tombs98/M3SNet
공식 코드A Mountain-Shaped Single-Stage Network for Accurate Image Restoration
https://github.com/ToniCreswell/Adversarial-Attack-On-Latent-Space
공식 코드https://github.com/TonyLianLong/CrossMAE
공식 코드https://github.com/TooTouch/REVECA
공식 코드REVECA -- Rich Encoder-decoder framework for Video Event CAptioner
https://github.com/TotalVariation/Flattenet
공식 코드FlatteNet: A Simple Versatile Framework for Dense Pixelwise Prediction
https://github.com/TsinghuaAI/CPM
공식 코드CPM-2: Large-scale Cost-effective Pre-trained Language Models
https://github.com/UARK-AICV/3DConvCaps
공식 코드3DConvCaps: 3DUnet with Convolutional Capsule Encoder for Medical Image Segmentation
https://github.com/UARK-AICV/AerialFormer
공식 코드AerialFormer: Multi-resolution Transformer for Aerial Image Segmentation
https://github.com/UAws/CV-3315-Is-All-You-Need
공식 코드https://github.com/UM-ARM-Lab/probabilistic_shape_completion
공식 코드Diverse Plausible Shape Completions from Ambiguous Depth Images
https://github.com/UTokyo-FieldPhenomics-Lab/corepp
공식 코드High-throughput 3D shape completion of potato tubers on a harvester
https://github.com/Ucas-HaoranWei/Vary
공식 코드Vary: Scaling up the Vision Vocabulary for Large Vision-Language Models
https://github.com/Uehwan/I-Keyboard
공식 코드I-Keyboard: Fully Imaginary Keyboard on Touch Devices Empowered by Deep Neural Decoder
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.