most citedHigh-Quality Entity Segmentation and Grounding

3 citations · 3 across the 3 of their papers we have counts for

collaborators

8 papers

cs.CV2026

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…

cs.CV2026

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…

cs.CV20263 cited

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…

cs.CV2026

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…

cs.CV2025

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…

cs.CV2025

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…