2 citations · 3 across the 2 of their papers we have counts for
3 papers
cs.CV2026★ 1 cited
VIPaint: Image Inpainting with Pre-Trained Diffusion Models via Variational Inference
Sakshi Agarwal, Gabriel Hope, Jimin Heo +1
Diffusion probabilistic models learn to remove noise added during training, generating novel data (e.g., images) from Gaussian noise through sequential denoising. However, conditio…
cs.HC2026★ 2 cited
"It's trained by non-disabled people": Evaluating How Image Quality Affects Product Captioning with Vision-Language Models
Kapil Garg, Xinru Tang, Jimin Heo +4
Vision-Language Models (VLMs) are increasingly used by blind and low-vision (BLV) people to identify and understand products in their everyday lives, such as food, personal care it…
cs.LG2025
Learning to be Smooth: An End-to-End Differentiable Particle Smoother
Ali Younis, Erik B. Sudderth
For challenging state estimation problems arising in domains like vision and robotics, particle-based representations attractively enable temporal reasoning about multiple posterio…