collaborators

6 papers

cs.CV2025

CholecInstanceSeg: A Tool Instance Segmentation Dataset for Laparoscopic Surgery

Oluwatosin Alabi, Ko Ko Zayar Toe, Zijian Zhou +4

In laparoscopic and robotic surgery, precise tool instance segmentation is an essential technology for advanced computer-assisted interventions. Although publicly available procedu…

cs.CV2025

MPDrive: Improving Spatial Understanding with Marker-Based Prompt Learning for Autonomous Driving

Zhiyuan Zhang, Xiaofan Li, Zhihao Xu +4

Autonomous driving visual question answering (AD-VQA) aims to answer questions related to perception, prediction, and planning based on given driving scene images, heavily relying…

cs.CV2024

Enhancing Generalized Few-Shot Semantic Segmentation via Effective Knowledge Transfer

Xinyue Chen, Miaojing Shi, Zijian Zhou +2

Generalized few-shot semantic segmentation (GFSS) aims to segment objects of both base and novel classes, using sufficient samples of base classes and few samples of novel classes.…

cs.CV2024

SEG-SAM: Semantic-Guided SAM for Unified Medical Image Segmentation

Shuangping Huang, Hao Liang, Qingfeng Wang +3

Recently, developing unified medical image segmentation models gains increasing attention, especially with the advent of the Segment Anything Model (SAM). SAM has shown promising b…

cs.CV2024

OpenPSG: Open-set Panoptic Scene Graph Generation via Large Multimodal Models

Zijian Zhou, Zheng Zhu, Holger Caesar +1

Panoptic Scene Graph Generation (PSG) aims to segment objects and recognize their relations, enabling the structured understanding of an image. Previous methods focus on predicting…

cs.CV2024

VLPrompt: Vision-Language Prompting for Panoptic Scene Graph Generation

Zijian Zhou, Miaojing Shi, Holger Caesar

Panoptic Scene Graph Generation (PSG) aims at achieving a comprehensive image understanding by simultaneously segmenting objects and predicting relations among objects. However, th…