2 citations · 5 across the 8 of their papers we have counts for
8 papers
A Unified Reasoning Framework for Holistic Zero-Shot Video Anomaly Analysis
Dongheng Lin, Mengxue Qu, Kunyang Han +3
Most video-anomaly research stops at frame-wise detection, offering little insight into why an event is abnormal, typically outputting only frame-wise anomaly scores without spatia…
3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation
Wenxin Chen, Mengxue Qu, Weitai Kang +3
3D Referring Expression Segmentation (3D-RES) typically requires extensive instance-level annotations, which are time-consuming and costly. Semi-supervised learning (SSL) mitigates…
ROSE: Revolutionizing Open-Set Dense Segmentation with Patch-Wise Perceptual Large Multimodal Model
Kunyang Han, Yibo Hu, Mengxue Qu +3
Advances in CLIP and large multimodal models (LMMs) have enabled open-vocabulary and free-text segmentation, yet existing models still require predefined category prompts, limiting…
ChatVTG: Video Temporal Grounding via Chat with Video Dialogue Large Language Models
Mengxue Qu, Xiaodong Chen, Wu Liu +2
Video Temporal Grounding (VTG) aims to ground specific segments within an untrimmed video corresponding to the given natural language query. Existing VTG methods largely depend on…
ACTRESS: Active Retraining for Semi-supervised Visual Grounding
Weitai Kang, Mengxue Qu, Yunchao Wei +1
Semi-Supervised Visual Grounding (SSVG) is a new challenge for its sparse labeled data with the need for multimodel understanding. A previous study, RefTeacher, makes the first att…
Intent3D: 3D Object Detection in RGB-D Scans Based on Human Intention
Weitai Kang, Mengxue Qu, Jyoti Kini +3
In real-life scenarios, humans seek out objects in the 3D world to fulfill their daily needs or intentions. This inspires us to introduce 3D intention grounding, a new task in 3D o…
RIO: A Benchmark for Reasoning Intention-Oriented Objects in Open Environments
Mengxue Qu, Yu Wu, Wu Liu +4
Intention-oriented object detection aims to detect desired objects based on specific intentions or requirements. For instance, when we desire to "lie down and rest", we instinctive…
SiRi: A Simple Selective Retraining Mechanism for Transformer-based Visual Grounding
Mengxue Qu, Yu Wu, Wu Liu +5
In this paper, we investigate how to achieve better visual grounding with modern vision-language transformers, and propose a simple yet powerful Selective Retraining (SiRi) mechani…