5 papers
End-to-End Autoregressive Image Generation with 1D Semantic Tokenizer
Wenda Chu, Bingliang Zhang, Jiaqi Han +4
Autoregressive image modeling relies on visual tokenizers to compress images into compact latent representations. We design an end-to-end training pipeline that jointly optimizes r…
InverseBench: Benchmarking Plug-and-Play Diffusion Priors for Inverse Problems in Physical Sciences
Hongkai Zheng, Wenda Chu, Bingliang Zhang +9
Plug-and-play diffusion priors (PnPDP) have emerged as a promising research direction for solving inverse problems. However, current studies primarily focus on natural image restor…
Improving Diffusion Inverse Problem Solving with Decoupled Noise Annealing
Bingliang Zhang, Wenda Chu, Julius Berner +3
Diffusion models have recently achieved success in solving Bayesian inverse problems with learned data priors. Current methods build on top of the diffusion sampling process, where…
STeP: A Framework for Solving Scientific Video Inverse Problems with Spatiotemporal Diffusion Priors
Bingliang Zhang, Zihui Wu, Berthy T. Feng +3
Reconstructing spatially and temporally coherent videos from time-varying measurements is a fundamental challenge in many scientific domains. A major difficulty arises from the spa…
Principled Probabilistic Imaging using Diffusion Models as Plug-and-Play Priors
Zihui Wu, Yu Sun, Yifan Chen +3
Diffusion models (DMs) have recently shown outstanding capabilities in modeling complex image distributions, making them expressive image priors for solving Bayesian inverse proble…