8 citations · 8 across the 5 of their papers we have counts for
5 papers
GeoAlign: Geometric Feature Realignment for MLLM Spatial Reasoning
Zhaochen Liu, Limeng Qiao, Guanglu Wan +1
Multimodal large language models (MLLMs) have exhibited remarkable performance in various visual tasks, yet still struggle with spatial reasoning. Recent efforts mitigate this by i…
Beyond the Visible: Benchmarking Occlusion Perception in Multimodal Large Language Models
Zhaochen Liu, Kaiwen Gao, Shuyi Liang +4
Occlusion perception, a critical foundation for human-level spatial understanding, embodies the challenge of integrating visual recognition and reasoning. Though multimodal large l…
Amodal Segmentation for Laparoscopic Surgery Video Instruments
Ruohua Shi, Zhaochen Liu, Lingyu Duan +1
Segmentation of surgical instruments is crucial for enhancing surgeon performance and ensuring patient safety. Conventional techniques such as binary, semantic, and instance segmen…
PLUG: Revisiting Amodal Segmentation with Foundation Model and Hierarchical Focus
Zhaochen Liu, Limeng Qiao, Xiangxiang Chu +1
Aiming to predict the complete shapes of partially occluded objects, amodal segmentation is an important step towards visual intelligence. With crucial significance, practical prio…
BLADE: Box-Level Supervised Amodal Segmentation through Directed Expansion
Zhaochen Liu, Zhixuan Li, Tingting Jiang
Perceiving the complete shape of occluded objects is essential for human and machine intelligence. While the amodal segmentation task is to predict the complete mask of partially o…