10 citations · 47 across the 33 of their papers we have counts for
8 papers · 1 filter
One Image is All You Need: Agentic One-Shot Image Generation via Text-Based World Models for Long-Tail Spatial Perception
Keqin Zeng, Shuting Su, Shihao Lin +2
Reliable spatial decision automation, such as autonomous driving and maritime surveillance, critically depends on robust visual perception. However, real-world spatiotemporal data…
GTR-Bench: Evaluating Geo-Temporal Reasoning in Vision-Language Models
Qinghongbing Xie, Zhaoyuan Xia, Feng Zhu +4
Recently spatial-temporal intelligence of Visual-Language Models (VLMs) has attracted much attention due to its importance for autonomous driving, embodied AI and general AI. Exist…
Language-Instructed Reasoning for Group Activity Detection via Multimodal Large Language Model
Jihua Peng, Qianxiong Xu, Yichen Liu +4
Group activity detection (GAD) aims to simultaneously identify group members and categorize their collective activities within video sequences. Existing deep learning-based methods…
SAMITE: Position Prompted SAM2 with Calibrated Memory for Visual Object Tracking
Qianxiong Xu, Lanyun Zhu, Chenxi Liu +4
Visual Object Tracking (VOT) is widely used in applications like autonomous driving to continuously track targets in videos. Existing methods can be roughly categorized into templa…
Unlocking the Power of SAM 2 for Few-Shot Segmentation
Qianxiong Xu, Lanyun Zhu, Xuanyi Liu +4
Few-Shot Segmentation (FSS) aims to learn class-agnostic segmentation on few classes to segment arbitrary classes, but at the risk of overfitting. To address this, some methods use…
Hybrid Mamba for Few-Shot Segmentation
Qianxiong Xu, Xuanyi Liu, Lanyun Zhu +4
Many few-shot segmentation (FSS) methods use cross attention to fuse support foreground (FG) into query features, regardless of the quadratic complexity. A recent advance Mamba can…
Eliminating Feature Ambiguity for Few-Shot Segmentation
Qianxiong Xu, Guosheng Lin, Chen Change Loy +3
Recent advancements in few-shot segmentation (FSS) have exploited pixel-by-pixel matching between query and support features, typically based on cross attention, which selectively…
VisionTraj: A Noise-Robust Trajectory Recovery Framework based on Large-scale Camera Network
Zhishuai Li, Ziyue Li, Xiaoru Hu +5
Trajectory recovery based on the snapshots from the city-wide multi-camera network facilitates urban mobility sensing and driveway optimization. The state-of-the-art solutions devo…