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Jinkun Hao

4 accepted papers

2026

STABLE: Simulation-Ready Tabletop Layout Generation via a Semantics–Physics Dual System

ICML 2026poster

Generating simulation-ready tabletop scenes from task instructions is an intriguing and promising research direction in the field of Embodied AI. However, existing task-to-scene generation methods rely exclusively on large language models (LLMs) to predict scene layouts, inevitably yielding object c…

Cited by 0SourceScholar
2025

ID-Sculpt: ID-aware 3D Head Generation from Single In-the-wild Portrait Image

AAAI 2025technical

While recent works have achieved great success on one-shot 3D common object generation, high quality and fidelity 3D head generation from a single image remains a great challenge. Previous text-based methods for generating 3D heads were limited by text descriptions and image-based methods struggled…

Cited by 0SourcePDFScholar
2025

MesaTask: Towards Task-Driven Tabletop Scene Generation via 3D Spatial Reasoning

NeurIPS 2025spotlight

The ability of robots to interpret human instructions and execute manipulation tasks necessitates the availability of task-relevant tabletop scenes for training. However, traditional methods for creating these scenes rely on time-consuming manual layout design or purely randomized layouts, which are…

Cited by 0SourceScholar
2025

Stylized-Face: A Million-level Stylized Face Dataset for Face Recognition

ICCV 2025poster

Stylized face recognition is the task of recognizing generated faces with the same ID across diverse stylistic domains (e.g., anime, painting, cyberpunk styles). This emerging field plays a vital role in the governance of generative image, serving the primary objective: Recognize the ID information…