3 citations · 4 across the 9 of their papers we have counts for
10 papers
Enhancing In-context Panoramic Generation via Geometric-aware Pretraining
Haoran Feng, Ruiyang Zhang, Longyi Zhang +2
In this work, we present Canvas360, a two-stage framework for in-context panoramic generation that combines geometry-aware pretraining with downstream task-specific fine-tuning. To…
UniSHARP: Universal Sharp Monocular View Synthesis
Meixi Song, Dizhe Zhang, Hao Ren +4
In this work, we focus on extending SHARP, the popular photorealistic view synthesis method, for universal monocular rendering across a continuum of camera systems, from convention…
Report of the 5th PVUW Challenge: Towards More Diverse Modalities in Pixel-Level Understanding
Chang Liu, Henghui Ding, Nikhila Ravi +40
This report summarizes the objectives, datasets, and top-performing methodologies of the 2026 Pixel-level Video Understanding in the Wild (PVUW) Challenge, hosted at CVPR 2026, whi…
Restage4D: Reanimating Deformable 3D Reconstruction from a Single Video
Jixuan He, Chieh Hubert Lin, Lu Qi +1
Creating deformable 3D content has gained increasing attention with the rise of text-to-image and image-to-video generative models. While these models provide rich semantic priors…
Learning Deblurring Texture Prior from Unpaired Data with Diffusion Model
Chengxu Liu, Lu Qi, Jinshan Pan +2
Since acquiring large amounts of realistic blurry-sharp image pairs is difficult and expensive, learning blind image deblurring from unpaired data is a more practical and promising…
Frequency Domain-Based Diffusion Model for Unpaired Image Dehazing
Chengxu Liu, Lu Qi, Jinshan Pan +2
Unpaired image dehazing has attracted increasing attention due to its flexible data requirements during model training. Dominant methods based on contrastive learning not only intr…
Unified Dense Prediction of Video Diffusion
Lehan Yang, Lu Qi, Xiangtai Li +3
We present a unified network for simultaneously generating videos and their corresponding entity segmentation and depth maps from text prompts. We utilize colormap to represent ent…
High-Quality Entity Segmentation and Grounding
Lu Qi, Yi-Wen Chen, Tao Zhang +4
In this work, we propose ESG, a pipeline for high-quality entity segmentation and grounding supported by a new dataset EntitySeg. At first, the proposed dataset naming EntitySeg co…
UniGS: Unified Representation for Image Generation and Segmentation
Lu Qi, Lehan Yang, Weidong Guo +4
This paper introduces a novel unified representation of diffusion models for image generation and segmentation. Specifically, we use a colormap to represent entity-level masks, add…
CSL: Class-Agnostic Structure-Constrained Learning for Segmentation Including the Unseen
Hao Zhang, Fang Li, Lu Qi +2
Addressing Out-Of-Distribution (OOD) Segmentation and Zero-Shot Semantic Segmentation (ZS3) is challenging, necessitating segmenting unseen classes. Existing strategies adapt the c…