Search Results for author:
Found 11 papers, 7 papers with code
A Noise is Worth Diffusion Guidance
Observing that noise obtained via diffusion inversion can reconstruct high-quality images without guidance, we focus on the initial noise of the denoising pipeline.
ControlFace: Harnessing Facial Parametric Control for Face Rigging
Manipulation of facial images to meet specific controls such as pose, expression, and lighting, also known as face rigging, is a complex task in computer vision.
Preference Consistency Matters: Enhancing Preference Learning in Language Models with Automated Self-Curation of Training Corpora
Inconsistent annotations in training corpora, particularly within preference learning datasets, pose challenges in developing advanced language models.
Improving Instruction Following in Language Models through Proxy-Based Uncertainty Estimation
Assessing response quality to instructions in language models is vital but challenging due to the complexity of human language across different contexts.
Self-Rectifying Diffusion Sampling with Perturbed-Attention Guidance
These techniques are often not applicable in unconditional generation or in various downstream tasks such as image restoration.
Retrieval-Augmented Score Distillation for Text-to-3D Generation
We leverage the retrieved asset to incorporate its geometric prior in the variational objective and adapt the diffusion model's 2D prior toward view consistency, achieving drastic improvements in both geometry and fidelity of generated scenes.
Domain Generalization Using Large Pretrained Models with Mixture-of-Adapters
Our focus in this study is on leveraging the knowledge of large pretrained models to improve handling of OOD scenarios and tackle domain generalization problems.
Ranked #1 on
Domain Generalization
on Office-Home
User-friendly Image Editing with Minimal Text Input: Leveraging Captioning and Injection Techniques
From the users' standpoint, prompt engineering is a labor-intensive process, and users prefer to provide a target word for editing instead of a full sentence.
Let 2D Diffusion Model Know 3D-Consistency for Robust Text-to-3D Generation
Text-to-3D generation has shown rapid progress in recent days with the advent of score distillation, a methodology of using pretrained text-to-2D diffusion models to optimize neural radiance field (NeRF) in the zero-shot setting.
DAG: Depth-Aware Guidance with Denoising Diffusion Probabilistic Models
Generative models have recently undergone significant advancement due to the diffusion models.
