Research
I'm interested in physiscs-based vision, computational imaging and computer graphics.
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Real-Time Intermediate Flow Estimation for Video Frame Interpolation
Zhewei Huang,
Tianyuan Zhang,
Wen Heng, Boxin Shi, Shuchang Zhou
ECCV, 2022
github
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arXiv
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demos
We propose a real-time intermediate flow estimation (RIFE) method for video frame interpolation, it
runs 30+FPS
for 2X 720p interpolation on a 2080Ti GPU
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Embracing Single Stride 3D Object Detector with Sparse Transformer
Lue Fan, Ziqi Pang,
Tianyuan Zhang,
Yu-Xiong Wang, Hang Zhao, Feng Wang, Naiyang Wang, Zhaoxiang Zhang
CVPR, 2022
github /
arxiv /
In contrast to 2D, object size in 3D does not exhibit long-tail distributions. We propose a single
stride sparse Transformer (SST) for 3D object detection. We obtained impressive results on small
objects
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DETR3D: 3D Object Detection from Multi-view Images via 3D-to-2D Queries
Yue Wang, Vitor Guizilini*,
Tianyuan Zhang*,
Yilun Wang, Hang Zhao, Justin Solomon
CoRL, 2021
github /
arxiv /
A new paradigm of 3D object detection from multiview 2D images
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MUTR3D: A Multi-camera Tracking Framework via 3D-to-2D Queries
Tianyuan Zhang,
Xuanyao Chen,
Yue Wang, Yilun Wang, Hang Zhao
preprint, 2022
project page
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github /
arXiv
End-to-End 3D tracking with multiview-cameras
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FUTR3D: A Unified Sensor Fusion Framework for 3D Detection
Xuanyao Chen,
Tianyuan Zhang,
Yue Wang, Yilun Wang, Hang Zhao
preprint, 2022
project page
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github /
arXiv
A unified framework for 3D detection from multi-sensor data. We achieved impressive results with
multiview-cameras and one-beam LiDAR.
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Objects365: A Large-scale, High-quality Dataset for Object Detection
Shuai Shao*, Zeming Li*,
Tianyuan Zhang*,
Chao Peng*, Gang Yu, Xiangyu Zhang, Jing Li, Jian Sun
ICCV, 2019
project page /
paper
We provide a high-quality large-scale object detection dataset, with 365
categories, 638K images,
and 10,101K bounding boxes
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You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle
Dinghuai Zhang*,
Tianyuan Zhang*,
Yiping Lu*, Zhanxing Zhu, Bin Dong
NeurIPS, 2019  
arXiv
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code
Accelerating adversarial training using Pontryagin`s Maximum Principle
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Interpreting Adversarially Trained Convolutional Neural Networks
Tianyuan Zhang,
Zhanxing Zhu
ICML, 2019
github /
arXiv
Discussion on the shape-bias and texture-bias of adversarially trainined convolutional neural
networks
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Professional Services
Program Committee member / Reviewer: CVPR' 2021, NeurIPS' 2020, ICLR' 2021
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