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cs.CV2026

StructGen: Disambiguating Multi-Reference Image Generation via Structured Context Modeling

Jianing Peng, Mengyu Wang, Henghui Ding +6

Multi-reference image generation aims to synthesize images by integrating attributes from multiple reference images under textual instructions. As the number of references increase…

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

CharaConsist: Fine-Grained Consistent Character Generation

Mengyu Wang, Henghui Ding, Jianing Peng +3

In text-to-image generation, producing a series of consistent contents that preserve the same identity is highly valuable for real-world applications. Although a few works have exp…

cs.CV2025

PVUW 2025 Challenge Report: Advances in Pixel-level Understanding of Complex Videos in the Wild

Henghui Ding, Chang Liu, Nikhila Ravi +33

This report provides a comprehensive overview of the 4th Pixel-level Video Understanding in the Wild (PVUW) Challenge, held in conjunction with CVPR 2025. It summarizes the challen…

cs.CV2024

Learning Trimaps via Clicks for Image Matting

Chenyi Zhang, Yihan Hu, Henghui Ding +3

Despite significant advancements in image matting, existing models heavily depend on manually-drawn trimaps for accurate results in natural image scenarios. However, the process of…

cs.CV2024

LSVOS Challenge Report: Large-scale Complex and Long Video Object Segmentation

Henghui Ding, Lingyi Hong, Chang Liu +30

Despite the promising performance of current video segmentation models on existing benchmarks, these models still struggle with complex scenes. In this paper, we introduce the 6th…