Chongjian GE 葛崇剑 rhettgee1995@gmail.com Google Scholar Github San Jose, California, USA

Biography

I am a Research Scientist at Adobe Research, working on visual generation models. In 2024, I got my Ph.D. degree from the CS Department, the University of Hong Kong, under the supervision of Prof. Ping Luo. I was also a visiting student at UC Berkeley, working with Prof. Masayoshi Tomizuka. We are actively hiring self-motivated interns. Please feel free to reach me if you are interested in interns at Adobe Research or collaborating with me.

News

Publications

	Goku: Flow Based Video Generative Foundation Models, Shoufa Chen*, Chongjian Ge*, Yuqi Zhang, Yida Zhang, Fengda Zhu, Hao Yang, Hongxiang Hao, Hui Wu, Zhichao Lai, Yifei Hu, Ting-Che Lin, Shilong Zhang, Fu Li, Chuan Li, Xing Wang, Yanghua Peng, Peize Sun, Ping Luo, Yi Jiang, Zehuan Yuan, Bingyue Peng, Xiaobing Liu IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR Highlight) 2025 [paper|project page|github]
	CompGS: Unleashing 2D Compositionality for Compositional Text-to-3D via Dynamically Optimizing 3D Gaussians, Chongjian Ge, Chenfeng Xu, Yuanfeng Ji, Chensheng Peng, Masayoshi Tomizuka, Ping Luo, Mingyu Ding+, Varun Jampani+, Wei Zhan IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2025 [project page]
	PixArt-Σ: Weak-to-Strong Training of Diffusion Transformer for 4K Text-to-Image Generation, Junsong Chen*, Chongjian Ge*, Enze Xie*, Yue Wu*, Lewei Yao, Xiaozhe Ren, Zhongdao Wang, Ping Luo, Huchuan Lu, Zhenguo Li European Conference on Computer Vision (ECCV) 2024 [paper|code|project page|media report]
	PIXART-α: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis, Junsong Chen*, Jincheng Yu*, Chongjian Ge*, Lewei Yao*, Enze Xie, Yue Wu, Zhongdao Wang, James Kwok, Ping Luo, Huchuan Lu, Zhenguo Li International Conference on Learning Representations (ICLR) 2024 (Spotlight) [paper|code|project page|media report]
	MetaBEV: Solving Sensor Failures for BEV Detection and Map Segmentation, Chongjian Ge*, Junsong Chen*, Enze Xie, Zhongdao Wang, Lanqing Hong, Huchuan Lu, Zhenguo Li, Ping Luo IEEE/CVF International Conference on Computer Vision (ICCV) 2023 [paper|project page|code|demo|chinese media report]
	Advancing Vision Transformers with Group-Mix Attention, Chongjian Ge, Xiaohan Ding, Zhan Tong, Li Yuan, Jiangliu Wang, Yibing Song, Ping Luo [paper|code|project page]
	Large Language Models as Automated Aligners for benchmarking Vision-Language Models, Yuanfeng Ji*, Chongjian Ge*, Weikai Kong, Enze Xie, Zhengying Liu, Zhengguo Li, Ping Luo International Conference on Learning Representations (ICLR) 2024 [paper|code (coming soom)|project page (coming soom)]
	Soft Neighbors Are Positive Supporters in Contrastive Visual Representation Learning, Chongjian Ge, Jiangliu Wang, Zhan Tong, Shoufa Chen, Yibing Song, and Ping Luo International Conference on Learning Representations (ICLR) 2023 [paper|code]
	Revitalizing CNN Attentions via Transformers in Self-Supervised Visual Representation Learning, Chongjian Ge, Youwei Liang, Yibing Song, Jianbo Jiao, Jue Wang, and Ping Luo Advances in Neural Information Processing Systems (NeurIPS) 2021 [paper|code|media report]
	Disentangled Cycle Consistency for Highly-realistic Virtual Try-On, Chongjian Ge, Yibing Song, Yuying Ge, Han Yang, Wei Liu, and Ping Luo IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2021 [paper|code]
	Rethinking Attentive Object Detection via Neural Attention Learning, Chongjian Ge, Yibing Song, Chao Ma, Yuankai Qi and Ping Luo JOURNAL OF IEEE TRANSACTIONS ON IMAGE PROCESSING (TIP) [paper]
	AdaptFormer: Adapting Vision Transformers for Scalable Visual Recognition, Shoufa Chen*, Chongjian Ge*, Zhan Tong, Jiangliu Wang, Yibing Song, Jue Wang, and Ping Luo Advances in Neural Information Processing Systems (NeurIPS) 2022 [paper|code|project page]
	Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations, Youwei Liang, Chongjian Ge, Zhan Tong, Yibing Song, Jue Wang, and Pengtao Xie International Conference on Learning Representations (ICLR) 2022 (Spotlight) [paper|code]
	CycleMLP: A MLP-like Architecture for Dense Prediction, Shoufa Chen, Enze Xie, Chongjian Ge, Runjian Chen, Ding Liang, and Ping Luo International Conference on Learning Representations (ICLR) 2022 (Oral) [paper|code|media report]
	CycleMLP: A MLP-like Architecture for Dense Visual Predictions, Shoufa Chen, Enze Xie, Chongjian Ge, Runjian Chen, Ding Liang, and Ping Luo IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2023 [paper|code]
	Parser-Free Virtual Try-on via Distilling Appearance Flows, Yuying Ge, Yibing Song, Ruimao Zhang, Chongjian Ge, Wei Liu, and Ping Luo IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2021 [paper|code]
	Watch Only Once: An End-to-End Video Action Detection Framework, Shoufa Chen, Peize Sun, Enze Xie, Chongjian Ge, Jiannan Wu, Lan Ma, Jiajun Shen, and Ping Luo IEEE/CVF International Conference on Computer Vision (ICCV) 2021 [paper|code]
	DeepAccident: A Motion and Accident Prediction Benchmark for V2X Autonomous Driving, Tianqi Wang, Sukmin Kim, Wenxuan Ji, Enze Xie, Chongjian Ge, Junsong Chen, Zhenguo Li, Ping Luo The Association for the Advancement of Artificial Intelligence (AAAI) 2023 [paper|homepage]
	InstructDET: Diversifying Referring Object Detection with Generalized Instructions, Ronghao Dang, Jiangyan Feng, Haodong Zhang, Chongjian Ge, Lin Song, Lijun Gong, Chengju Liu, Qijun Chen, Feng Zhu, Rui Zhao, Yibing Song International Conference on Learning Representations (ICLR) 2024 [paper|code]
	AMOS: A Large-Scale Abdominal Multi-Organ Benchmark for Versatile Medical Image Segmentation, Yuanfeng Ji, Haotian Bai, Chongjian Ge, Jie Yang, Ye Zhu, Ruimao Zhang, Zhen Li, Lingyan Zhang, Wanling Ma, Xiang Wan, Ping Luo Advances in Neural Information Processing Systems (NeurIPS 2022 Track Datasets and Benchmarks) (Oral) [paper|project page]

Honors and Awards

Academic Service