collaborators

7 papers

cs.CV2026

Knowledge Visualization: A Benchmark and Method for Knowledge-Intensive Text-to-Image Generation

Ran Zhao, Sheng Jin, Size Wu +5

Recent text-to-image (T2I) models have demonstrated impressive capabilities in photorealistic synthesis and instruction following. However, their reliability in knowledge-intensive…

cs.CV2026

Thinking with Camera: A Unified Multimodal Model for Camera-Centric Understanding and Generation

Kang Liao, Size Wu, Zhonghua Wu +6

Camera-centric understanding and generation are two cornerstones of spatial intelligence, yet they are typically studied in isolation. We present Puffin, a unified camera-centric m…

cs.CV2025

Controllable Human-centric Keyframe Interpolation with Generative Prior

Zujin Guo, Size Wu, Zhongang Cai +2

Existing interpolation methods use pre-trained video diffusion priors to generate intermediate frames between sparsely sampled keyframes. In the absence of 3D geometric guidance, t…

cs.CV2025

OpenUni: A Simple Baseline for Unified Multimodal Understanding and Generation

Size Wu, Zhonghua Wu, Zerui Gong +5

In this report, we present OpenUni, a simple, lightweight, and fully open-source baseline for unifying multimodal understanding and generation. Inspired by prevailing practices in…

cs.CV2025

Harmonizing Visual Representations for Unified Multimodal Understanding and Generation

Size Wu, Wenwei Zhang, Lumin Xu +6

Unifying visual understanding and generation within a single multimodal framework remains a significant challenge, as the two inherently heterogeneous tasks require representations…

cs.CV2025

F-LMM: Grounding Frozen Large Multimodal Models

Size Wu, Sheng Jin, Wenwei Zhang +4

Endowing Large Multimodal Models (LMMs) with visual grounding capability can significantly enhance AIs' understanding of the visual world and their interaction with humans. However…