6 citations · 7 across the 3 of their papers we have counts for
3 papers
cs.CV2024★ 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.LG2020
Learning Consistent Deep Generative Models from Sparse Data via Prediction Constraints
Gabriel Hope, Madina Abdrakhmanova, Xiaoyin Chen +2
We develop a new framework for learning variational autoencoders and other deep generative models that balances generative and discriminative goals. Our framework optimizes model p…
cs.CV2017★ 6 cited
Cascaded Scene Flow Prediction using Semantic Segmentation
Zhile Ren, Deqing Sun, Jan Kautz +1
Given two consecutive frames from a pair of stereo cameras, 3D scene flow methods simultaneously estimate the 3D geometry and motion of the observed scene. Many existing approaches…