7 citations · 25 across the 37 of their papers we have counts for
33 papers · 1 filter
Models as Tools: An Agentic Coordination Framework for Unified Multimodal Visual Tracking
Wenrui Cai, Yuzhe Li, Qingjie Liu +1
Most current visual trackers adopt a matching-based architecture trained exclusively on tracking datasets, whose performance gains depend heavily on the length of the input context…
Reasoning-Driven Anomaly Detection and Localization with Image-Level Supervision
Yizhou Jin, Yuezhu Feng, Jinjin Zhang +3
Multimodal large language models (MLLMs) have recently demonstrated remarkable reasoning and perceptual abilities for anomaly detection. However, most approaches remain confined to…
Uni-MDTrack: Learning Decoupled Memory and Dynamic States for Parameter-Efficient Visual Tracking in All Modality
Wenrui Cai, Zhenyi Lu, Yuzhe Li +4
With the advent of Transformer-based one-stream trackers that possess strong capability in inter-frame relation modeling, recent research has increasingly focused on how to introdu…
ResWorld: Temporal Residual World Model for End-to-End Autonomous Driving
Jinqing Zhang, Zehua Fu, Zelin Xu +3
The comprehensive understanding capabilities of world models for driving scenarios have significantly improved the planning accuracy of end-to-end autonomous driving frameworks. Ho…
Beyond Open Vocabulary: Multimodal Prompting for Object Detection in Remote Sensing Images
Shuai Yang, Ziyue Huang, Jiaxin Chen +2
Open-vocabulary object detection in remote sensing commonly relies on text-only prompting to specify target categories, implicitly assuming that inference-time category queries can…
AttriPrompt: Dynamic Prompt Composition Learning for CLIP
Qiqi Zhan, Shiwei Li, Qingjie Liu +1
The evolution of prompt learning methodologies has driven exploration of deeper prompt designs to enhance model performance. However, current deep text prompting approaches suffer…
De-Simplifying Pseudo Labels to Enhancing Domain Adaptive Object Detection
Zehua Fu, Chenguang Liu, Yuyu Chen +3
Despite its significant success, object detection in traffic and transportation scenarios requires time-consuming and laborious efforts in acquiring high-quality labeled data. Ther…
SeriesBench: A Benchmark for Narrative-Driven Drama Series Understanding
Chenkai Zhang, Yiming Lei, Zeming Liu +5
With the rapid development of Multi-modal Large Language Models (MLLMs), an increasing number of benchmarks have been established to evaluate the video understanding capabilities o…
Towards Robust and Controllable Text-to-Motion via Masked Autoregressive Diffusion
Zongye Zhang, Bohan Kong, Qingjie Liu +1
Generating 3D human motion from text descriptions remains challenging due to the diverse and complex nature of human motion. While existing methods excel within the training distri…
SkeletonX: Data-Efficient Skeleton-based Action Recognition via Cross-sample Feature Aggregation
Zongye Zhang, Wenrui Cai, Qingjie Liu +1
While current skeleton action recognition models demonstrate impressive performance on large-scale datasets, their adaptation to new application scenarios remains challenging. Thes…
Vision-Language Model for Object Detection and Segmentation: A Review and Evaluation
Yongchao Feng, Yajie Liu, Shuai Yang +13
Vision-Language Model (VLM) have gained widespread adoption in Open-Vocabulary (OV) object detection and segmentation tasks. Despite they have shown promise on OV-related tasks, th…
A Survey on Remote Sensing Foundation Models: From Vision to Multimodality
Ziyue Huang, Hongxi Yan, Qiqi Zhan +7
The rapid advancement of remote sensing foundation models, particularly vision and multimodal models, has significantly enhanced the capabilities of intelligent geospatial data int…
OpenRSD: Towards Open-prompts for Object Detection in Remote Sensing Images
Ziyue Huang, Yongchao Feng, Shuai Yang +3
Remote sensing object detection has made significant progress, but most studies still focus on closed-set detection, limiting generalization across diverse datasets. Open-vocabular…
SPMTrack: Spatio-Temporal Parameter-Efficient Fine-Tuning with Mixture of Experts for Scalable Visual Tracking
Wenrui Cai, Qingjie Liu, Yunhong Wang
Most state-of-the-art trackers adopt one-stream paradigm, using a single Vision Transformer for joint feature extraction and relation modeling of template and search region images.…
PACF: Prototype Augmented Compact Features for Improving Domain Adaptive Object Detection
Chenguang Liu, Yongchao Feng, Yanan Zhang +2
In recent years, there has been significant advancement in object detection. However, applying off-the-shelf detectors to a new domain leads to significant performance drop, caused…
LightOcc: Lightweight Spatial Embedding for Efficient Vision-based 3D Occupancy Prediction
Jinqing Zhang, Yanan Zhang, Wenrui Cai +2
Occupancy prediction has garnered increasing attention in recent years for its comprehensive fine-grained environmental representation and strong generalization to open-set objects…
ONER: Online Experience Replay for Incremental Anomaly Detection
Yizhou Jin, Jiahui Zhu, Guodong Wang +5
Incremental anomaly detection aims to sequentially identify defects in industrial product lines but suffers from catastrophic forgetting, primarily due to knowledge overwriting dur…
GeoBEV: Learning Geometric BEV Representation for Multi-view 3D Object Detection
Jinqing Zhang, Yanan Zhang, Yunlong Qi +3
Bird's-Eye-View (BEV) representation has emerged as a mainstream paradigm for multi-view 3D object detection, demonstrating impressive perceptual capabilities. However, existing me…
MutDet: Mutually Optimizing Pre-training for Remote Sensing Object Detection
Ziyue Huang, Yongchao Feng, Qingjie Liu +1
Detection pre-training methods for the DETR series detector have been extensively studied in natural scenes, e.g., DETReg. However, the detection pre-training remains unexplored in…
FSD-BEV: Foreground Self-Distillation for Multi-view 3D Object Detection
Zheng Jiang, Jinqing Zhang, Yanan Zhang +4
Although multi-view 3D object detection based on the Bird's-Eye-View (BEV) paradigm has garnered widespread attention as an economical and deployment-friendly perception solution f…
Semantic Enhanced Few-shot Object Detection
Zheng Wang, Yingjie Gao, Qingjie Liu +1
Few-shot object detection~(FSOD), which aims to detect novel objects with limited annotated instances, has made significant progress in recent years. However, existing methods stil…
YOLC: You Only Look Clusters for Tiny Object Detection in Aerial Images
Chenguang Liu, Guangshuai Gao, Ziyue Huang +3
Detecting objects from aerial images poses significant challenges due to the following factors: 1) Aerial images typically have very large sizes, generally with millions or even hu…
Generic Knowledge Boosted Pre-training For Remote Sensing Images
Ziyue Huang, Mingming Zhang, Yuan Gong +2
Deep learning models are essential for scene classification, change detection, land cover segmentation, and other remote sensing image understanding tasks. Most backbones of existi…
Towards Generalizable Referring Image Segmentation via Target Prompt and Visual Coherence
Yajie Liu, Pu Ge, Haoxiang Ma +4
Referring image segmentation (RIS) aims to segment objects in an image conditioning on free-from text descriptions. Despite the overwhelming progress, it still remains challenging…