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Text to Image Generation
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/oneThousand1000/Portrait3D
공식 코드https://github.com/onethousand1000/animportrait3d
공식 코드Text-based Animatable 3D Avatars with Morphable Model Alignment
https://github.com/open-mmlab/anycontrol
공식 코드AnyControl: Create Your Artwork with Versatile Control on Text-to-Image Generation
https://github.com/openai/DALL-E
공식 코드https://github.com/openbmb/viscpm
공식 코드Large Multilingual Models Pivot Zero-Shot Multimodal Learning across Languages
https://github.com/opengvlab/instruct2act
공식 코드Instruct2Act: Mapping Multi-modality Instructions to Robotic Actions with Large Language Model
https://github.com/oppo-mente-lab/facescore
공식 코드FaceScore: Benchmarking and Enhancing Face Quality in Human Generation
https://github.com/oppo-mente-lab/x2i
공식 코드https://github.com/optml-group/advunlearn
공식 코드Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models
https://github.com/optml-group/unlearncanvas
공식 코드UnlearnCanvas: Stylized Image Dataset for Enhanced Machine Unlearning Evaluation in Diffusion Models
https://github.com/orangesodahub/scenecraft
공식 코드https://github.com/paint4poem/paint4poem
공식 코드Paint4Poem: A Dataset for Artistic Visualization of Classical Chinese Poems
https://github.com/pals-ttic/sjc
공식 코드Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generation
https://github.com/patchwork53/asymmetricattack
공식 코드Asymmetric Bias in Text-to-Image Generation with Adversarial Attacks
https://github.com/pengbo807/ConditionVideo
공식 코드ConditionVideo: Training-Free Condition-Guided Text-to-Video Generation
https://github.com/perf-project/PeRF
공식 코드PERF: Panoramic Neural Radiance Field from a Single Panorama
https://github.com/pioneerAlpha/BanglaText2ImageGeneration
공식 코드https://github.com/pku-dair/hetu
공식 코드Accelerating Text-to-Image Editing via Cache-Enabled Sparse Diffusion Inference
https://github.com/pku-yuangroup/imgedit
공식 코드https://github.com/pku-yuangroup/wise
공식 코드WISE: A World Knowledge-Informed Semantic Evaluation for Text-to-Image Generation
https://github.com/pkunliu/isotropic3d
공식 코드Isotropic3D: Image-to-3D Generation Based on a Single CLIP Embedding
https://github.com/pluslabnlp/vp-csv
공식 코드Character-Centric Story Visualization via Visual Planning and Token Alignment
https://github.com/pmh9960/GCDP
공식 코드https://github.com/pmh9960/regft-for-gen
공식 코드Regularized Training with Generated Datasets for Name-Only Transfer of Vision-Language Models
https://github.com/preethiseshadri518/bias-amplification-paradox
공식 코드https://github.com/q-future/q-refine
공식 코드G-Refine: A General Quality Refiner for Text-to-Image Generation
https://github.com/qihao067/direct3d
공식 코드DIRECT-3D: Learning Direct Text-to-3D Generation on Massive Noisy 3D Data
https://github.com/qualcomm-ai-research/clockwork-diffusion
공식 코드Clockwork Diffusion: Efficient Generation With Model-Step Distillation
https://github.com/rang1991/public-intermediate-semantics-for-generation
공식 코드Generating Intermediate Representations for Compositional Text-To-Image Generation
https://github.com/recklessronan/muse
공식 코드https://github.com/redaigc/storymaker
공식 코드StoryMaker: Towards Holistic Consistent Characters in Text-to-image Generation
https://github.com/researchmm/generate-it
공식 코드Unifying Multimodal Transformer for Bi-directional Image and Text Generation
https://github.com/rinongal/textual_inversion
공식 코드An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion
https://github.com/rmpku/cpdm
공식 코드A Dataset and Benchmark for Copyright Infringement Unlearning from Text-to-Image Diffusion Models
https://github.com/rockeycoss/spo
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.