1 citations · 1 across the 5 of their papers we have counts for
5 papers
Contrastive Visual Data Augmentation
Yu Zhou, Bingxuan Li, Mohan Tang +6
Large multimodal models (LMMs) often struggle to recognize novel concepts, as they rely on pre-trained knowledge and have limited ability to capture subtle visual details. Domain-s…
InSpaceType: Dataset and Benchmark for Reconsidering Cross-Space Type Performance in Indoor Monocular Depth
Cho-Ying Wu, Quankai Gao, Chin-Cheng Hsu +3
Indoor monocular depth estimation helps home automation, including robot navigation or AR/VR for surrounding perception. Most previous methods primarily experiment with the NYUv2 D…
VDebugger: Harnessing Execution Feedback for Debugging Visual Programs
Xueqing Wu, Zongyu Lin, Songyan Zhao +4
Visual programs are executable code generated by large language models to address visual reasoning problems. They decompose complex questions into multiple reasoning steps and invo…
DACO: Towards Application-Driven and Comprehensive Data Analysis via Code Generation
Xueqing Wu, Rui Zheng, Jingzhen Sha +6
Data analysis is a crucial analytical process to generate in-depth studies and conclusive insights to comprehensively answer a given user query for tabular data. In this work, we a…
Planning as In-Painting: A Diffusion-Based Embodied Task Planning Framework for Environments under Uncertainty
Cheng-Fu Yang, Haoyang Xu, Te-Lin Wu +3
Task planning for embodied AI has been one of the most challenging problems where the community does not meet a consensus in terms of formulation. In this paper, we aim to tackle t…