Ju He

I am currently an Applied Scientist at Amazon Frontier AI & Robotics (FAR). Previously, I worked as a Research Scientist at ByteDance Seed.

I received my Ph.D. in Computer Science from Johns Hopkins University, where I was advised by Bloomberg Distinguished Professor Alan L. Yuille. Prior to that, I earned my B.S. in Computer Science from Peking University.

Email / Google Scholar

News

FlowTok, MaskGen, RAR and xAR have been accepted to ICCV 2025! See you at Honolulu!

Publications

Full list on Google Scholar Profile

	FlowTok: Flowing Seamlessly Across Text and Image Tokens Ju He, Qihang Yu, Qihao Liu, Liang-Chieh Chen In International Conference on Computer Vision (ICCV), 2025 arXiv / code / project page
	Democratizing Text-to-Image Masked Generative Models with Compact Text-Aware One-Dimensional Tokens Dongwon Kim, Ju He, Qihang Yu, Chenglin Yang, Xiaohui Shen, Suha Kwak, Liang-Chieh Chen In International Conference on Computer Vision (ICCV), 2025* arXiv / code / project page
	Randomized Autoregressive Visual Generation Qihang Yu, Ju He, Xueqing Deng, Xiaohui Shen, Liang-Chieh Chen In International Conference on Computer Vision (ICCV), 2025 arXiv / code / project page
	Beyond Next-Token: Next-X Prediction for Autoregressive Visual Generation Sucheng Ren, Qihang Yu, Ju He, Xiaohui Shen, Alan Yuille, Liang-Chieh Chen In International Conference on Computer Vision (ICCV), 2025 arXiv / code / project page
	Alleviating Distortion in Image Generation via Multi-Resolution Diffusion Models Qihao Liu, Zhanpeng Zeng, Ju He, Qihang Yu, Xiaohui Shen, Liang-Chieh Chen In Neural Information Processing Systems (NeurIPS), 2024* arXiv / code / project page
	A Simple Video Segmenter by Tracking Objects Along Axial Trajectories Ju He, Qihang Yu, Inkyu Shin, Xueqing Deng, Alan Yuille, Xiaohui Shen, Liang-Chieh Chen In Transactions on Machine Learning Research (TMLR), 2024 arXiv / code
	Convolutions Die Hard: Open-Vocabulary Segmentation with Single Frozen Convolutional CLIP Qihang Yu, Ju He, Xueqing Deng, Xiaohui Shen, Liang-Chieh Chen In Neural Information Processing Systems (NeurIPS), 2023 arXiv / code
	Compositor: Bottom-up Clustering and Compositing for Robust Part and Object Segmentation Ju He, Jieneng Chen, Mingxian, Lin, Qihang Yu, Alan Yuille In Conference on Computer Vision and Pattern Recognition (CVPR), 2023 arXiv / code
	CORL: Compositional Representation Learning for Few-Shot Classification Ju He, Adam Kortylewski, Alan Yuille In Winter Conference on Applications of Computer Vision (WACV), 2023 arXiv
	PartImageNet: A Large, High-Quality Dataset of Parts Ju He, Shuo Yang, Shaokang Yang, Adam Kortylewski, Xiaoding Yuan, Jieneng Chen, Shuai Liu, Cheng Yang, Qihang Yu, Alan Yuille In European Conference on Computer Vision (ECCV), 2022 arXiv / code
	TransFG: A Transformer Architecture for Fine-grained Recognition Ju He, Jieneng Chen, Shuai Liu, Adam Kortylewski, Cheng Yang, Yutong Bai, Changhu Wang, Alan Yuille In Association for the Advancement of Artificial Intelligence (AAAI), 2022 arXiv / code
	Semi-synthesis: A fast way to produce effective datasets for stereo matching Ju He, Enyu Zhou, Liusheng Sun, Fei Lei, Chenyang Liu, Wenxiu Sun In Conference on Computer Vision and Pattern Recognition Workshop (CVPRW), 2021 arXiv
	Compositional Convolutional Neural Networks: A Deep Architecture with Innate Robustness to Partial Occlusion Adam Kortylewski, Ju He, Qing Liu, Alan Yuille In Conference on Computer Vision and Pattern Recognition (CVPR), 2020 arXiv / code

Last update: Oct. 2025 Template