← Search

Yaokun Li

7 accepted papers

2026

Diagram2Structure: Unlocking LLMs' Diagram Comprehension through DiagramDiff, a Framework for Structuring Offline Diagrams

CVPR 2026

Diagrams are widely used in daily life. However, offline diagrams typically exist in the form of images, lacking structured data representation, which significantly limits their reusability and editability. Current research mainly focuses on supporting basic query tasks for online diagrams and does

Cited by 0SourceScholar
2026

DynamicTree: Interactive Real Tree Animation via Sparse Voxel Spectrum

CVPR 2026

Generating dynamic and interactive 3D trees has wide applications in virtual reality, games, and world simulation. However, existing methods still face various challenges in generating structurally consistent and realistic 4D motion for complex real trees. In this paper, we propose DynamicTree, the

Cited by 0SourcecodeScholar
2026

FullPart: Generating each 3D Part at Full Resolution

ICLR 2026poster

Part-based 3D generation holds great potential for various applications. Previous part generators that represent parts using implicit vector-set tokens often suffer from insufficient geometric details. Another line of work adopts an explicit voxel representation but shares a global voxel grid among…

Cited by 0SourcecodeScholar
2026

Resolving the Stability-Plasticity Dilemma in Reinforcement Learning via Complementary Continual Critics

CVPR 2026

This paper proposes the Continual Dual-Critic with Cross-Attention (CD-CCA) framework for visual reinforcement learning to address the plasticity-stability conflict. Our method introduces continual learning techniques into the visual RL architecture, constructing two complementary critics using Cont

Cited by 0SourcecodeScholar
2025

Exploiting Continuous Motion Clues for Vision-Based Occupancy Prediction

AAAI 2025technical

Occupancy networks aim to reconstruct the surroundings with occupied semantic voxels. However, frequent object occlusions often occur in dynamic real-world scenarios, which cannot be captured by independent frames. Most existing occupancy networks generate results without explicitly considering past…

2025

From One to More: Contextual Part Latents for 3D Generation

ICCV 2025poster

To generate 3D objects, early research focused on multi-view-driven approaches relying solely on 2D renderings. Recently, the 3D native latent diffusion paradigm has demonstrated superior performance in 3D generation, because it fully leverages the geometric information provided in ground truth 3D d…

2024

SpaceGTN: A Time-Agnostic Graph Transformer Network for Handwritten Diagram Recognition and Segmentation

AAAI 2024technical

Online handwriting recognition is pivotal in domains like note-taking, education, healthcare, and office tasks. Existing diagram recognition algorithms mainly rely on the temporal information of strokes, resulting in a decline in recognition performance when dealing with notes that have been modifie…

Cited by 2SourcePDFScholar