https://github.com/asaakyan/explain-st
공식 코드ICLEF: In-Context Learning with Expert Feedback for Explainable Style Transfer
Papers with Code 아카이브
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ashkanpakzad/atn
공식 코드https://github.com/asindel/artfacepoints
공식 코드ArtFacePoints: High-resolution Facial Landmark Detection in Paintings and Prints
https://github.com/askerlee/lapstyle
공식 코드https://github.com/astonzhang/Parameterization-of-Hypercomplex-Multiplications
공식 코드https://github.com/astra-vision/poda
공식 코드https://github.com/auspicious3000/SpeechSplit
공식 코드Unsupervised Speech Decomposition via Triple Information Bottleneck
https://github.com/awei669/VQ-Font
공식 코드https://github.com/azadis/MC-GAN
공식 코드https://github.com/bandainamcoresearchinc/bandai-namco-research-motiondataset
공식 코드Motion Capture Dataset for Practical Use of AI-based Motion Editing and Stylization
https://github.com/bardhprenkaj/gist
공식 코드https://github.com/barisbatuhan/dass_det_inference
공식 코드Domain-Adaptive Self-Supervised Pre-Training for Face & Body Detection in Drawings
https://github.com/barisbatuhan/dass_detector
공식 코드Domain-Adaptive Self-Supervised Pre-Training for Face & Body Detection in Drawings
https://github.com/barisgecer/facegan
공식 코드https://github.com/behavioral-data/PARTNER
공식 코드https://github.com/bgalerne/scaling_painting_style_transfer
공식 코드https://github.com/birdortyedi/cifr-pytorch
공식 코드Patch-wise Contrastive Style Learning for Instagram Filter Removal
https://github.com/birdortyedi/denim
공식 코드Deterministic Neural Illumination Mapping for Efficient Auto-White Balance Correction
https://github.com/birdortyedi/instagram-filter-removal-pytorch
공식 코드https://github.com/boeun-kim/most
공식 코드MoST: Motion Style Transformer between Diverse Action Contents
https://github.com/boschresearch/issa
공식 코드Intra- & Extra-Source Exemplar-Based Style Synthesis for Improved Domain Generalization
https://github.com/bottlecapper/EmoMUNIT
공식 코드https://github.com/bovifocr/tcdiff
공식 코드TCDiff: Triple Condition Diffusion Model with 3D Constraints for Stylizing Synthetic Faces
https://github.com/byungsook/neural-flow-style
공식 코드https://github.com/cai-jianfeng/flowmind2digital
공식 코드Flowmind2Digital: The First Comprehensive Flowmind Recognition and Conversion Approach
https://github.com/cc-hpc-itwm/facialgan
공식 코드FacialGAN: Style Transfer and Attribute Manipulation on Synthetic Faces
https://github.com/cesaremagnetti/automaticusnavigation
공식 코드Cross Modality 3D Navigation Using Reinforcement Learning and Neural Style Transfer
https://github.com/chahuja/mix-stage
공식 코드Style Transfer for Co-Speech Gesture Animation: A Multi-Speaker Conditional-Mixture Approach
https://github.com/chandagrover/sem-cs
공식 코드Sem-CS: Semantic CLIPStyler for Text-Based Image Style Transfer
https://github.com/chaofengc/Face-Sketch
공식 코드Face Sketch Synthesis with Style Transfer using Pyramid Column Feature
https://github.com/chaofengc/Face-Sketch-Wild
공식 코드Semi-Supervised Learning for Face Sketch Synthesis in the Wild
https://github.com/chaofengc/PSFRGAN
공식 코드Progressive Semantic-Aware Style Transformation for Blind Face Restoration
https://github.com/chendaryen/artfusion
공식 코드ArtFusion: Controllable Arbitrary Style Transfer using Dual Conditional Latent Diffusion Models
https://github.com/chenyingshu/advances_3d_neural_stylization
공식 코드https://github.com/chiutaiyin/PhotoWCT2
공식 코드https://github.com/chiutaiyin/pca-knowledge-distillation
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.