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Junqiu Yu

4 accepted papers

2026

Re^3Sim: Generating High-Fidelity Simulation Data Via 3D-Photorealistic Real-To-Sim for Robotic Manipulation

ICRA 2026poster

Real-world data collection for robotics is costly and resource-intensive, requiring skilled operators and expensive hardware. Simulations offer a scalable alternative but often fail to achieve sim-to-real generalization due to geometric and visual gaps. To address these challenges, we propose a 3D-p…

Cited by 0Scholar
2026

Spatially Guided Training for Vision-Language-Action Model

ICLR 2026poster

Large vision–language models (VLMs) excel at multimodal understanding but fall short when extended to embodied tasks, where instructions must be transformed into low-level motor actions. We introduce SP-VLA, a dual-system **V**ision–**L**anguage–**A**ction framework that leverages **S**patial **P**r…

Cited by 0SourceScholar
2025

Towards Enhanced Image Inpainting: Mitigating Unwanted Object Insertion and Preserving Color Consistency

CVPR 2025highlight

Recent advances in image inpainting increasingly use generative models to handle large irregular masks. However, these models can create unrealistic inpainted images due to two main issues: (1) Unwanted object insertion: Even with unmasked areas as context, generative models may still generate arbit…

2024

Polaris: Open-ended Interactive Robotic Manipulation via Syn2Real Visual Grounding and Large Language Models

IROS 2024poster

This paper investigates the task of the open-ended interactive robotic manipulation on table-top scenarios. While recent Large Language Models (LLMs) enhance robots' comprehension of user instructions, their lack of visual grounding constrains their ability to physically interact with the environmen…

Cited by 4SourcecodeScholar