Chao Feng
I am a first-year CSE PhD student at the University of Michigan (UMich).
Email: chfeng at umich dot edu
Google Scholar  / 
Github
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Research
I'm interested in computer vision and multimodal learning. Please see Google Scholar.
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GPS-to-3D: Lifting Tourist Photos to 3D Using 2D GPS-Conditioned Diffusion
Chao Feng,
Ziyang Chen,
Aleksander Holynski,
Alexei A. Efros,
Andrew Owens,
In submission
We produce 3D reconstruction for landmarks from unordered collections of tourist photos by GPS conditioned diffusion model and score distillation sampling.
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Binding Touch to Everything: Learning Unified Multimodal Tactile Representations
Fengyu Yang*,
Chao Feng*,
Ziyang Chen*,
Hyoungseob Park,
Daniel Wang,
Yiming Dou,
Ziyao Zeng,
Xien Chen,
Rit Gangopadhyay,
Andrew Owens,
Alex Wong,
CVPR, 2024
project page /
paper
We introduce UniTouch, a unified tactile representation for vision-based tactile sensors aligned with multiple modalities. We show we can now use powerful models trained on other modalities (e.g. CLIP, LLM) to conduct tactile sensing tasks zero shot.
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This&That: Language-Gesture Controlled Video Generation for Robot Planning
Boyang Wang ,
Nikhil Sridhar,
Chao Feng,
Mark Van der Merwe,
Adam Fishman,
Nima Fazeli,
Jeong Joon Park,
In submission
project page /
paper
We introduce This&That, a framework that generates videos from text instructions and gestures for robot planning.
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Vision-Flan: Scaling Human-Labeled Tasks in Visual Instruction Tuning
Zhiyang Xu,
Chao Feng,
Rulin Shao,
Trevor Ashby,
Ying Shen,
Di Jin,
Yu Cheng,
Qifan Wang,
Lifu Huang,
ACL, 2024 (Findings)
project page /
paper
We construct Vision-Flan, the most diverse publicly available visual instruction tuning dataset to date.
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Self-Supervised Video Forensics by Audio-Visual Anomaly Detection
Chao Feng,
Ziyang Chen,
Andrew Owens,
CVPR, 2023   (Highlight)
project page
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arXiv
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code
We learn several feature sets in a self-supervised manner by using audio-visual synchronization task and utilize autoregressive model to do anomaly detection on top of each feature set for video forensics detection.
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AVA-AVD: Audio-Visual Speaker Diarization in the Wild
Eric Zhongcong Xu,
Zeyang Song,
Satoshi Tsutsui,
Chao Feng,
Mang Ye,
Mike Zheng Shou,
ACM Multimedia, 2022
project page
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arXiv
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code
We create the AVA Audio-Visual Diarization (AVA-AVD) dataset to develop diarization methods for in-the-wild videos.
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Service
CVPR 2022/2024, WACV 2023, ACM MM 2023, ICCV 2023, ECCV 2024, NeurIPS 2024, ICRA 2025, ICLR 2025, AISTATS 2025, TPAMI.
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