Papers with Code 아카이브
Text to Image Generation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 1
- 평가표
- 1
- 보존된 평가 기록
- 0
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/rongyaofang/puma
공식 코드PUMA: Empowering Unified MLLM with Multi-granular Visual Generation
https://github.com/royira/syntax-guided-generation
공식 코드https://github.com/rt219/latentguard
공식 코드Latent Guard: a Safety Framework for Text-to-image Generation
https://github.com/ruchikachavhan/concept-prune
공식 코드ConceptPrune: Concept Editing in Diffusion Models via Skilled Neuron Pruning
https://github.com/ruihangao/tactiledreamfusion
공식 코드Tactile DreamFusion: Exploiting Tactile Sensing for 3D Generation
https://github.com/rvignav/diffusion-tts
공식 코드Test-Time Scaling of Diffusion Models via Noise Trajectory Search
https://github.com/sachit-menon/generating-illustrated-instructions-reproduction
공식 코드https://github.com/sadil13/vln-ram
공식 코드https://github.com/sail-sg/consistent3d
공식 코드https://github.com/sairin1202/vp-csv
공식 코드Character-Centric Story Visualization via Visual Planning and Token Alignment
https://github.com/sais-fuxi/evalalign
공식 코드https://github.com/salanueva/sr4g
공식 코드https://github.com/salesforce/lavis
공식 코드https://github.com/sbyebss/monge_map_solver
공식 코드https://github.com/schuture/benchmarking-awesome-diffusion-models
공식 코드https://github.com/senmaoy/RAT-Diffusion
공식 코드Data Extrapolation for Text-to-image Generation on Small Datasets
https://github.com/seungjucha/verbdiff
공식 코드VerbDiff: Text-Only Diffusion Models with Enhanced Interaction Awareness
https://github.com/shahariar-shibli/adversarial-attack-on-pos-tags
공식 코드Adversarial Attacks on Parts of Speech: An Empirical Study in Text-to-Image Generation
https://github.com/share424/indonesian-text-to-image-synthesis-with-sentence-bert-and-fastgan
공식 코드Indonesian Text-to-Image Synthesis with Sentence-BERT and FastGAN
https://github.com/shengcheng/captions4t2i
공식 코드Precision or Recall? An Analysis of Image Captions for Training Text-to-Image Generation Model
https://github.com/shi-labs/forget-me-not
공식 코드Forget-Me-Not: Learning to Forget in Text-to-Image Diffusion Models
https://github.com/shihaozhaozsh/lavi-bridge
공식 코드Bridging Different Language Models and Generative Vision Models for Text-to-Image Generation
https://github.com/shihongl1998/llm-as-a-blackbox-optimizer
공식 코드Language Models as Black-Box Optimizers for Vision-Language Models
https://github.com/shiml20/flowturbo
공식 코드FlowTurbo: Towards Real-time Flow-Based Image Generation with Velocity Refiner
https://github.com/shizhediao/davinci
공식 코드Write and Paint: Generative Vision-Language Models are Unified Modal Learners
https://github.com/showlab/evolvedirector
공식 코드EvolveDirector: Approaching Advanced Text-to-Image Generation with Large Vision-Language Models
https://github.com/shuangquanfeng/fergi
공식 코드https://github.com/simeonallmendinger/syntheticimagegeneration
공식 코드https://github.com/sisidai/InterFusion
공식 코드InterFusion: Text-Driven Generation of 3D Human-Object Interaction
https://github.com/slark-prime/maai_optimizer
공식 코드https://github.com/smile365317/abp
공식 코드Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation
https://github.com/sofeeyaj/poetry-in-pixels-coling2025
공식 코드Poetry in Pixels: Prompt Tuning for Poem Image Generation via Diffusion Models
https://github.com/softrepa/SoftREPA
공식 코드Aligning Text to Image in Diffusion Models is Easier Than You Think
https://github.com/songweige/rich-text-to-image
공식 코드https://github.com/sreyan88/aspire
공식 코드ASPIRE: Language-Guided Data Augmentation for Improving Robustness Against Spurious Correlations
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.