97 citations · 123 across the 9 of their papers we have counts for
10 papers
Retrieving Any Relevant Moments: Benchmark and Models for Generalized Moment Retrieval
Yiming Ding, Siyu Cao, Luyuan Jiao +4
Video Moment Retrieval (VMR) aims to localize temporal segments in videos that correspond to a natural language query, but typically assumes only a single matching moment for each…
FiCoTS: Fine-to-Coarse LLM-Enhanced Hierarchical Cross-Modality Interaction for Time Series Forecasting
Yafei Lyu, Hao Zhou, Lu Zhang +2
Time series forecasting is central to data analysis and web technologies. The recent success of Large Language Models (LLMs) offers significant potential for this field, especially…
Boosting Open-Vocabulary Object Detection by Handling Background Samples
Ruizhe Zeng, Lu Zhang, Xu Yang +1
Open-vocabulary object detection is the task of accurately detecting objects from a candidate vocabulary list that includes both base and novel categories. Currently, numerous open…
Refined Pseudo labeling for Source-free Domain Adaptive Object Detection
Siqi Zhang, Lu Zhang, Zhiyong Liu
Domain adaptive object detection (DAOD) assumes that both labeled source data and unlabeled target data are available for training, but this assumption does not always hold in real…
FIT: Frequency-based Image Translation for Domain Adaptive Object Detection
Siqi Zhang, Lu Zhang, Zhiyong Liu +1
Domain adaptive object detection (DAOD) aims to adapt the detector from a labelled source domain to an unlabelled target domain. In recent years, DAOD has attracted massive attenti…
Automatically Discovering Novel Visual Categories with Self-supervised Prototype Learning
Lu Zhang, Lu Qi, Xu Yang +3
This paper tackles the problem of novel category discovery (NCD), which aims to discriminate unknown categories in large-scale image collections. The NCD task is challenging due to…
Zero-shot object goal visual navigation
Qianfan Zhao, Lu Zhang, Bin He +2
Object goal visual navigation is a challenging task that aims to guide a robot to find the target object based on its visual observation, and the target is limited to the classes p…
Weakly Aligned Feature Fusion for Multimodal Object Detection
Lu Zhang, Zhiyong Liu, Xiangyu Zhu +4
To achieve accurate and robust object detection in the real-world scenario, various forms of images are incorporated, such as color, thermal, and depth. However, multimodal data of…
Unseen Object Instance Segmentation with Fully Test-time RGB-D Embeddings Adaptation
Lu Zhang, Siqi Zhang, Xu Yang +2
Segmenting unseen objects is a crucial ability for the robot since it may encounter new environments during the operation. Recently, a popular solution is leveraging RGB-D features…
Weakly Aligned Cross-Modal Learning for Multispectral Pedestrian Detection
Lu Zhang, Xiangyu Zhu, Xiangyu Chen +3
Multispectral pedestrian detection has shown great advantages under poor illumination conditions, since the thermal modality provides complementary information for the color image.…