1 code implementation • 30 Nov 2023 • Tianwei Yin, Michaël Gharbi, Richard Zhang, Eli Shechtman, Fredo Durand, William T. Freeman, Taesung Park
We introduce Distribution Matching Distillation (DMD), a procedure to transform a diffusion model into a one-step image generator with minimal impact on image quality.
1 code implementation • 17 May 2023 • Guangxuan Xiao, Tianwei Yin, William T. Freeman, Frédo Durand, Song Han
FastComposer proposes delayed subject conditioning in the denoising step to maintain both identity and editability in subject-driven image generation.
Ranked #7 on Diffusion Personalization Tuning Free on AgeDB
no code implementations • 25 Apr 2023 • Zihui Wu, Tianwei Yin, Yu Sun, Robert Frost, Andre van der Kouwe, Adrian V. Dalca, Katherine L. Bouman
Traditional CS-MRI methods often separately address measurement subsampling, image reconstruction, and task prediction, resulting in a suboptimal end-to-end performance.
1 code implementation • CVPR 2022 • Xingyi Zhou, Tianwei Yin, Vladlen Koltun, Philipp Krähenbühl
The transformer encodes object features from all frames, and uses trajectory queries to group them into trajectories.
Ranked #13 on Multi-Object Tracking on SportsMOT (using extra training data)
1 code implementation • NeurIPS 2021 • Tianwei Yin, Xingyi Zhou, Philipp Krähenbühl
For autonomous driving, this means that large objects close to the sensors are easily visible, but far-away or small objects comprise only one measurement or two.
Ranked #63 on 3D Object Detection on nuScenes
1 code implementation • 13 May 2021 • Tianwei Yin, Zihui Wu, He Sun, Adrian V. Dalca, Yisong Yue, Katherine L. Bouman
In this paper, we leverage the sequential nature of MRI measurements, and propose a fully differentiable framework that jointly learns a sequential sampling policy simultaneously with a reconstruction strategy.
11 code implementations • CVPR 2021 • Tianwei Yin, Xingyi Zhou, Philipp Krähenbühl
Three-dimensional objects are commonly represented as 3D boxes in a point-cloud.
Ranked #1 on Robust 3D Object Detection on nuScenes-C
1 code implementation • 11 Mar 2018 • Sumanth Dathathri, Stephan Zheng, Tianwei Yin, Richard M. Murray, Yisong Yue
Deep neural networks are vulnerable to adversarial examples, which dramatically alter model output using small input changes.