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Found 5 papers, 2 papers with code
Domain Generalization Using Large Pretrained Models with Mixture-of-Adapters
By using both PEFT and MoA methods, we effectively alleviate the performance deterioration caused by distribution shifts and achieve state-of-the-art performance on diverse DG benchmarks.
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.
Improving Sample Quality of Diffusion Models Using Self-Attention Guidance
Denoising diffusion models (DDMs) have attracted attention for their exceptional generation quality and diversity.
