https://github.com/shs910/psst
공식 코드PSST: A Benchmark for Evaluation-driven Text Public-Speaking Style Transfer
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/shs910/tsst
공식 코드PSST: A Benchmark for Evaluation-driven Text Public-Speaking Style Transfer
https://github.com/silky1708/local-style-transfer
공식 코드https://github.com/silvia1993/HyMOS
공식 코드Distance-based Hyperspherical Classification for Multi-source Open-Set Domain Adaptation
https://github.com/sinmdm/sinmdm
공식 코드https://github.com/siyuhuang/quantart
공식 코드QuantArt: Quantizing Image Style Transfer Towards High Visual Fidelity
https://github.com/sjtuplayer/compositional_neural_painter
공식 코드Stroke-based Neural Painting and Stylization with Dynamically Predicted Painting Region
https://github.com/skoltech-nlp/detox
공식 코드https://github.com/skoltech-nlp/formality
공식 코드Detecting Text Formality: A Study of Text Classification Approaches
https://github.com/skoltech-nlp/multilingual_detox
공식 코드Exploring Cross-lingual Textual Style Transfer with Large Multilingual Language Models
https://github.com/skoltech-nlp/rudetoxifier
공식 코드Methods for Detoxification of Texts for the Russian Language
https://github.com/skoltech-nlp/sgdd-tst
공식 코드Studying the role of named entities for content preservation in text style transfer
https://github.com/songrise/Artist
공식 코드DiffArtist: Towards Structure and Appearance Controllable Image Stylization
https://github.com/songrise/mllm4art
공식 코드https://github.com/sonnguyen129/deep-feature-rotation
공식 코드https://github.com/sooyyoungg/aesfa
공식 코드AesFA: An Aesthetic Feature-Aware Arbitrary Neural Style Transfer
https://github.com/sophiajw/HistAuGAN
공식 코드https://github.com/souro/multilingual_text_detoxification
공식 코드https://github.com/souro/multilingual_tst
공식 코드Multilingual Text Style Transfer: Datasets & Models for Indian Languages
https://github.com/souro/polarity-denoising-sentiment-transfer
공식 코드Balancing the Style-Content Trade-Off in Sentiment Transfer Using Polarity-Aware Denoising
https://github.com/souro/tst_llm
공식 코드Are Large Language Models Actually Good at Text Style Transfer?
https://github.com/sshan-zhao/GASDA
공식 코드Geometry-Aware Symmetric Domain Adaptation for Monocular Depth Estimation
https://github.com/strawberryfg/NAPA-NST-HPE
공식 코드https://github.com/stringtron/quantative_style
공식 코드https://github.com/sumuzhao/CycleGAN-Music-Style-Transfer
공식 코드https://github.com/sunniesuhyoung/DST
공식 코드https://github.com/sunshower76/deep_trainslation_prior
공식 코드Deep Translation Prior: Test-time Training for Photorealistic Style Transfer
https://github.com/suzgunmirac/crowd-sampling
공식 코드Follow the Wisdom of the Crowd: Effective Text Generation via Minimum Bayes Risk Decoding
https://github.com/suzgunmirac/prompt-and-rerank
공식 코드https://github.com/syw1996/SCIR-TG-Data2text-Bi-Aspect
공식 코드Learning to Select Bi-Aspect Information for Document-Scale Text Content Manipulation
https://github.com/tag-and-generate/Politeness-Transfer-A-Tag-and-Generate-Approach
공식 코드https://github.com/tangtaogo/lidar-nerf
공식 코드LiDAR-NeRF: Novel LiDAR View Synthesis via Neural Radiance Fields
https://github.com/tanyuqian/ctc-gen-eval
공식 코드https://github.com/taozhen1110/cat-llm
공식 코드https://github.com/tear-kitty/moedit
공식 코드MoEdit: On Learning Quantity Perception for Multi-object Image Editing
https://github.com/tencentarc/t2i-adapter
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.