Qihang Yu

I am a Research Scientist at ByteDance. Previously, I received my Ph.D. degree from Computer Science department at Johns Hopkins University, advised by Bloomberg Distinguished Professor Dr. Alan Yuille. I am a member of Computational Cognition, Vision, and Learning.

Before that, I obtained B.S. in Computer Science at Peking University in 2018.

Email / Google Scholar

News

2 paper accepted to NeurIPS 2023
1 paper accepted to WACV 2024 as Oral
1 paper accepted to ICCV 2023
1 paper accepted to CVPR 2023
1 paper accepted to ICLR 2023
2 paper accepted to ECCV 2022
2 paper accepted to CVPR 2022, with one as Oral

Research

My research lies in computer vision, deep learning, and medical image analysis.

	Convolutions Die Hard: Open-Vocabulary Segmentation with Single Frozen Convolutional CLIP Qihang Yu, Ju He, Xueqing Deng, Xiaohui Shen, Liang-Chieh Chen NeurIPS, 2023 paper / project page
	ReMaX: Relaxing for Better Training on Efficient Panoptic Segmentation Shuyang Sun, Weijun Wang, Qihang Yu, Andrew Howard, Philip Torr, Liang-Chieh Chen NeurIPS, 2023 paper
	Towards a Single Unified Model for Effective Detection, Segmentation, and Diagnosis of Eight Major Cancers Using a Large Collection of CT Scans Jieneng Chen, Yingda Xia, Jiawen Yao, Ke Yan, Jianpeng Zhang, Le Lu, Fakai Wang, Bo Zhou, Mingyan Qiu, Qihang Yu, Mingze Yuan, Wei Fang, Yuxing Tang, Minfeng Xu, Jian Zhou, Yuqian Zhao, Qifeng Wang, Xianghua Ye, Xiaoli Yin, Yu Shi, Xin Chen, Jingren Zhou, Alan Yuille, Zaiyi Liu, Ling Zhang ICCV, 2023 paper
	Video-kMaX: A Simple Unified Approach for Online and Near-Online Video Panoptic Segmentation Inkyu Shin, Dahun Kim, Qihang Yu, Jun Xie, Hong-Seok Kim, Bradley Green, In So Kweon, Kuk-Jin Yoon, Liang-Chieh Chen WACV, 2024 Oral paper
	A Study of Autoregressive Decoders for Multi-Tasking in Computer Vision Lucas Beyer, Bo Wan, Gagan Madan, Filip Pavetic, Andreas Steiner, Alexander Kolesnikov, Andre Susano Pinto, Emanuele Bugliarello, Xiao Wang, Qihang Yu, Liang-Chieh Chen, Xiaohua Zhai Tech report, arXiv paper
	Compositor: Bottom-up Clustering and Compositing for Robust Part and Object Segmentation Ju He, Jieneng Chen, Ming-Xian Lin, Qihang Yu, Alan Yuille CVPR, 2023 paper
	MOAT: Alternating Mobile Convolution and Attention Brings Strong Vision Models Chenglin Yang, Siyuan Qiao, Qihang Yu, Xiaoding Yuan, Yukun Zhu, Alan Yuille, Hartwig Adam, Liang-Chieh Chen ICLR, 2023 paper / project page
	k-means Mask Transformer Qihang Yu, Huiyu Wang, Siyuan Qiao, Maxwell Collins, Yukun Zhu, Hartwig Adam, Alan Yuille, Liang-Chieh Chen ECCV, 2022 paper / project page / pytorch reproduction / Google AI Blog
	PartImageNet: A Large, High-Quality Dataset of Parts Ju He, Shuo Yang, Shaokang Yang, Adam Kortylewski, Xiaoding Yuan, Jie-Neng Chen, Shuai Liu, Cheng Yang, Qihang Yu, Alan Yuille ECCV, 2022 paper / project page
	CMT-DeepLab: Clustering Mask Transformers for Panoptic Segmentation Qihang Yu, Huiyu Wang, Dahun Kim, Siyuan Qiao, Maxwell Collins, Yukun Zhu, Hartwig Adam, Alan Yuille, Liang-Chieh Chen CVPR, 2022 Oral paper / Google AI Blog
	TubeFormer-DeepLab: Video Mask Transformer Dahun Kim, Jun Xie, Huiyu Wang, Siyuan Qiao, Qihang Yu, Hong-Seok Kim, Hartwig Adam, In So Kweon, Liang-Chieh Chen CVPR, 2022 paper
	Glance-and-Gaze Vision Transformer Qihang Yu, Yingda Xia, Yutong Bai, Yongyi Lu, Alan Yuille, Wei Shen NeurIPS, 2021 paper / project page
	DeepLab2: A TensorFlow Library for Deep Labeling Mark Weber, Huiyu Wang, Siyuan Qiao, Jun Xie, Maxwell D. Collins, Yukun Zhu, Liangzhe Yuan, Dahun Kim, Qihang Yu, Daniel Cremers, Laura Leal-Taixe, Alan L. Yuille, Florian Schroff, Hartwig Adam, Liang-Chieh Chen Tech report*, arXiv paper / project page
	Mask Guided Matting via Progressive Refinement Network Qihang Yu, Jianming Zhang, He Zhang, Yilin Wang, Zhe Lin, Ning Xu, Yutong Bai, Alan Yuille CVPR, 2021 paper / project page
	TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation Jieneng Chen, Yongyi Lu, Qihang Yu, Xiangde Luo, Ehsan Adeli, Yan Wang, Le Lu, Alan Yuille, Yuyin Zhou Tech report, arXiv paper / project page
	Shape-Texture Debiased Neural Network Training Yingwei Li, Qihang Yu, Mingxing Tan, Jieru Mei, Peng Tang, Wei Shen, Alan Yuille, Cihang Xie ICLR, 2021 paper / project page
	CAKES: Channel-wise Automatic KErnel Shrinking for Efficient 3D Network Qihang Yu, Yingwei Li, Jieru Mei, Yuyin Zhou, Alan Yuille AAAI, 2021 paper / project page
	Can Temporal Information Help with Contrastive Self-Supervised Learning? Yutong Bai, Haoqi Fan, Ishan Misra, Ganesh Venkatesh, Yongyi Lu, Yuyin Zhou, Qihang Yu, Vikas Chandra, Alan Yuille Tech report, arXiv paper
	Detecting Pancreatic Adenocarcinoma in Multi-phase CT Scans via Alignment Ensemble Yingda Xia, Qihang Yu, Wei Shen, Yuyin Zhou, Elliot K Fishman, Alan Yuille MICCAI, 2020 paper
	C2FNAS: Coarse-to-Fine Neural Architecture Search for 3D Medical Image Segmentation Qihang Yu, Dong Yang, Holger Roth, Yutong Bai, Yixiao Zhang, Alan Yuille, Daguang Xu CVPR, 2020 paper
	Neural Architecture Search for Lightweight Non-Local Networks Yingwei Li, Xiaojie Jin, Jieru Mei, Xiaochen Lian, Linjie Yang, Cihang Xie, Qihang Yu, Yuyin Zhou, Song Bai, Alan Yuille CVPR, 2020 paper / project page
	When Radiology Report Generation Meets Knowledge Graph Yixiao Zhang, Xiaosong Wang, Ziyue Xu, Qihang Yu, Alan Yuille, Daguang Xu AAAI, 2020 paper
	Recurrent Saliency Transformation Network for Tiny Target Segmentation in Abdominal CT Scans Lingxi Xie, Qihang Yu, Yuyin Zhou, Yan Wang, Elliot K Fishman, Alan Yuille IEEE Transactions on Medical Imaging (TMI), 2019 paper
	Thickened 2D Networks for Efficient 3D Medical Image Segmentation Qihang Yu, Yingda Xia, Lingxi Xie, Elliot K Fishman, Alan Yuille Tech report, arxiv paper
	Recurrent Saliency Transformation Network: Incorporating Multi-Stage Visual Cues for Small Organ Segmentation Qihang Yu, Lingxi Xie, Yan Wang, Yuyin Zhou, Elliot K Fishman, Alan Yuille CVPR, 2018 paper / project page

Stolen from Jon Barron