https://github.com/isee-laboratory/dreamview
공식 코드DreamView: Injecting View-specific Text Guidance into Text-to-3D Generation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Image Generation (synthesis) is the task of generating new images from an existing dataset.
In this section, you can find state-of-the-art leaderboards for unconditional generation. For conditional generation, and other types of image generations, refer to the subtasks.
<span style="color:grey; opacity: 0.6">( Image credit: StyleGAN )</span>
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
DreamView: Injecting View-specific Text Guidance into Text-to-3D Generation
Langevin Autoencoders for Learning Deep Latent Variable Models
2S-ODIS: Two-Stage Omni-Directional Image Synthesis by Geometric Distortion Correction
Do Not Escape From the Manifold: Discovering the Local Coordinates on the Latent Space of GANs
RewardSDS: Aligning Score Distillation via Reward-Weighted Sampling
AITTI: Learning Adaptive Inclusive Token for Text-to-Image Generation
Unsupervised Image-to-Image Translation with Self-Attention Networks
Conditional Vector Graphics Generation for Music Cover Images
Diagnostic Benchmark and Iterative Inpainting for Layout-Guided Image Generation
DALL-Eval: Probing the Reasoning Skills and Social Biases of Text-to-Image Generation Models
ReCorD: Reasoning and Correcting Diffusion for HOI Generation
OmniFlow: Any-to-Any Generation with Multi-Modal Rectified Flows
PopAlign: Population-Level Alignment for Fair Text-to-Image Generation
Filtered-Guided Diffusion: Fast Filter Guidance for Black-Box Diffusion Models
Diffusion Models with Anisotropic Gaussian Splatting for Image Inpainting
Adversarial Learning of Disentangled and Generalizable Representations for Visual Attributes
Parts of Speech-Grounded Subspaces in Vision-Language Models
Slideflow: Deep Learning for Digital Histopathology with Real-Time Whole-Slide Visualization
ShapeLLM-Omni: A Native Multimodal LLM for 3D Generation and Understanding
How Well Does GPT-4V(ision) Adapt to Distribution Shifts? A Preliminary Investigation
AI-Driven Cytomorphology Image Synthesis for Medical Diagnostics
Generative Flows as a General Purpose Solution for Inverse Problems
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.