publications

2026

1. SIGGRAPH 2026

   

   MTPano: Multi-Task Panoramic Scene Understanding via Label-Free Integration of Dense Prediction Priors

   Jingdong Zhang, Xiaohang Zhan, Lingzhi Zhang, Yizhou Wang, Zhengming Yu, Jionghao Wang, Wenping Wang, and Xin Li

   In SIGGRAPH, 2026

   Abs arXiv HTML Code

   We propose a foundational panoramic scene understanding model capable of predicting multiple dense prediction tasks. We achieve this by i) curating large dataset with auto labeling pipeline by existing perspective prediction models, ii) propose PD-BridgeNet to tackle the multi-task interaction challenges under EPR distortions.

2. CVPR 2026

   

   UniSER: A Foundation Model for Unified Soft Effects Removal

   Jingdong Zhang, Lingzhi Zhang, Qing Liu, MangTik Chiu, Connelly Barnes, Yizhou Wang, Haoran You, Xiaoyang Liu, Yuqian Zhou, Zhe Lin, Eli Shechtman, Sohrab Amirghodsi, Xin Li, Wenping Wang, and Xiaohang Zhan

   In CVPR, 2026

   Abs arXiv HTML

   A foundational image soft effect removal model offering curated datasets, fine-grained user control via spatial masks, zero-shot generalization on unseen effects, and effect enhancement capabilities.

2025

1. CVPR 2025

   

   Layer- and Timestep-Adaptive Differentiable Token Compression Ratios for Efficient Diffusion Transformers

   Haoran You, Connelly Barnes, Yuqian Zhou, Yan Kang, Zhenbang Du, Wei Zhou, Lingzhi Zhang, Yotam Nitzan, Xiaoyang Liu, Zhe Lin, Eli Shechtman, Sohrab Amirghodsi, and Yingyan Celine Lin

   In CVPR, 2025

   PDF
2. CVPR 2025

   

   FineCaption: Compositional Image Captioning Focusing on Wherever You Want at Any Granularity

   Hang Hua, Qing Liu, Lingzhi Zhang, Jing Shi, Soo Ye Kim, Zhifei Zhang, Yilin Wang, Jianming Zhang, Zhe Lin, and Jiebo Luo

   In CVPR, 2025

   PDF
3. ICCV 2025

   

   Refer to Anything with Vision-Language Prompts

   Shengcao Cao, Zijun Wei, Jason Kuen, Kangning Liu, Lingzhi Zhang, Jiuxiang Gu, HyunJoon Jung, Liang-Yan Gui, and Yu-Xiong Wang

   In ICCV, 2025

   arXiv
4. ACL 2025

   

   Cautious Next Token Prediction

   Yizhou Wang, Lingzhi Zhang, Yue Bai, Mang Tik Chiu, Zhengmian Hu, Mingyuan Zhang, Qihua Dong, Yu Yin, Sohrab Amirghodsi, and Yun Fu

   In ACL Findings, 2025

   PDF
5. WACV 2025

   

   Fine-grained Defocus Blur Control for Generative Image Models

   Ayush Shrivastava, Connelly Barnes, Xuaner Zhang, Lingzhi Zhang, Andrew Owens, Sohrab Amirghodsi, and Eli Shechtman

   In WACV, 2025

   arXiv

2024

1. WACV 2024

   

   Good Seed Makes a Good Crop: Discovering Secret Seeds in Text-to-Image Diffusion Models

   Katherine Xu, Lingzhi Zhang, and Jianbo Shi

   In WACV, 2024

   HTML
2. WACV 2024

   

   Detecting Origin Attribution for Text-to-Image Diffusion Models

   Katherine Xu, Lingzhi Zhang, and Jianbo Shi

   In WACV, 2024

   PDF
3. CVPR 2024

   

   Brush2Prompt: Contextual Prompt Generator for Object Inpainting

   Mang Tik Chiu, Yuqian Zhou, Lingzhi Zhang, Zhe Lin, Connelly Barnes, Sohrab Amirghodsi, Eli Shechtman, and Humphrey Shi

   In CVPR, 2024

   PDF
4. CVPR 2024

   

   Amodal Completion via Progressive Mixed Context Diffusion

   Katherine Xu, Lingzhi Zhang, and Jianbo Shi

   In CVPR, 2024

   PDF

2023

1. ICCV 2023

   

   Perceptual Artifacts Localization for Image Synthesis Tasks

   Lingzhi Zhang, Zhengjie Xu, Connelly Barnes, Yuqian Zhou, Qing Liu, He Zhang, Zhe Lin, Eli Shechtman, Sohrab Amirghodsi, and Jianbo Shi

   In ICCV, 2023

   Abs arXiv Code

   We generalize Perceptual Artifacts Localization to ten diverse image synthesis tasks, and show promising accuracy. We also show the effectiveness of automatic artifacts fixing and quality assessment as downstream applications.

2022

1. ECCV 2022

   

   Perceptual Artifacts Localization for Inpainting

   Lingzhi Zhang, Yuqian Zhou, Connelly Barnes, Sohrab Amirghodsi, Zhe Lin, Eli Shechtman, and Jianbo Shi

   In ECCV, 2022

   Abs arXiv Code

   We formulate a new task of learning perceptual artifacts localization on the inpainted images. We propose a high-quality labeled dataset, successfully train a model to localize the perceptual artifacts, and demonstrate downstream practical applications to no-reference single image quality assessment and iterative fill.

2. ECCV 2022

   

   Inpainting at Modern Camera Resolution by Guided PatchMatch with Auto-Curation

   Lingzhi Zhang, Connelly Barnes, Kevin Wampler, Sohrab Amirghodsi, Eli Shechtman, Zhe Lin, and Jianbo Shi

   In ECCV, 2022

   Abs arXiv Code

   We propose a hybrid deep learning and patch-based approach for inpainting at modern camera resolution (4K+).

3. ECCV 2022

   

   Fine-Grained Egocentric Hand-Object Segmentation: Dataset, Model, and Applications

   Lingzhi Zhang, Shenghao Zhou, Simon Stent, and Jianbo Shi

   In ECCV, 2022

   Abs arXiv HTML Code

   We propose a fine-grained egocentric hand-object segmentation dataset and model, and demonstrate its usage to multiple downstream vision applications, such as activity recognition, hand-object reconstruction, and seeing through the hands in videos.

2020

1. ECCV 2020

   

   Learning Diverse Object Placement by Inpainting for Compositional Data Augmentation

   Lingzhi Zhang, Tarmily Wen, Jie Min, David Han, and Jianbo Shi

   In ECCV, 2020

   Abs PDF

   We study the problem of common sense placement of visual objects in an image.

2. CVPR 2020

   

   Nested Scale-Editing for Conditional Image Synthesis

   Lingzhi Zhang, Jiancong Wang, Yinshuang Xu, Jie Min, Tarmily Wen, James C. Gee, and Jianbo Shi

   In CVPR, 2020

   Abs PDF

   We proposed an image synthesis approach that provides stratified navigation in the latent code space.

3. WACV 2020

   

   Deep Image Blending

   Lingzhi Zhang, Tarmily Wen, and Jianbo Shi

   In WACV, 2020

   Abs arXiv Code

   We propose a deep optimization-based blending algorithm.

4. WACV 2020

   

   Multimodal Image Outpainting with Regularized Normalized Diversification

   Lingzhi Zhang, Jiancong Wang, and Jianbo Shi

   In WACV, 2020

   Abs arXiv Code

   We study the problem of generating a set of realistic and diverse backgrounds when given only a small foreground region, which we formulate as image outpainting task.

2019

1. NeurIPS-W 2019

   

   Neural Embedding for Physical Manipulations

   Lingzhi Zhang, Andong Cao, Rui Li, and Jianbo Shi

   In Machine Learning for Physical Science Workshop, NeurIPS, 2019

   Abs arXiv

   Inspired by the properties of grid cells in mammalian brains, we build a generative model that enforces a normalized pairwise distance constraint between the latent space and output space to achieve data-efficient discovery of output spaces.