91 citations · 155 across the 30 of their papers we have counts for
24 papers · 1 filter
AdaptVPR: Route-Aware Hard Positive Generation for Robust Visual Place Recognition
Shunpeng Chen, Jingyi Zhang, Changwei Wang +6
Visual Place Recognition (VPR) localizes a query image by retrieving database images of the same or nearby place, yet its robustness is often degraded by domain shifts arising from…
DeliCIR: Memory-Guided Test-Time Deliberation via Multi-Agent Collaboration for Composed Image Retrieval
Xingtian Pei, Yukun Song, Changwei Wang +4
Composed Image Retrieval (CIR) requires both preserving the visual continuity of the reference image and faithfully executing the semantic variables specified in the modification t…
Region Matters: Efficient and Reliable Region-Aware Visual Place Recognition
Shunpeng Chen, Yukun Song, Changwei Wang +6
Visual Place Recognition (VPR) determines a query image's geographic location by matching it against geotagged databases. However, existing methods struggle with perceptual aliasin…
MoFu: Scale-Aware Modulation and Fourier Fusion for Multi-Subject Video Generation
Run Ling, Ke Cao, Jian Lu +15
Multi-subject video generation aims to synthesize videos from textual prompts and multiple reference images, ensuring that each subject preserves natural scale and visual fidelity.…
Complementary Information Guided Occupancy Prediction via Multi-Level Representation Fusion
Rongtao Xu, Jinzhou Lin, Jialei Zhou +6
Camera-based occupancy prediction is a mainstream approach for 3D perception in autonomous driving, aiming to infer complete 3D scene geometry and semantics from 2D images. Almost…
CurriFlow: Curriculum-Guided Depth Fusion with Optical Flow-Based Temporal Alignment for 3D Semantic Scene Completion
Jinzhou Lin, Jie Zhou, Wenhao Xu +7
Semantic Scene Completion (SSC) aims to infer complete 3D geometry and semantics from monocular images, serving as a crucial capability for camera-based perception in autonomous dr…
SAGE: Spatial-visual Adaptive Graph Exploration for Efficient Visual Place Recognition
Shunpeng Chen, Changwei Wang, Rongtao Xu +7
Visual Place Recognition (VPR) requires robust retrieval of geotagged images despite large appearance, viewpoint, and environmental variation. Prior methods focus on descriptor fin…
Language-Driven Object-Oriented Two-Stage Method for Scene Graph Anticipation
Xiaomeng Zhu, Changwei Wang, Haozhe Wang +2
A scene graph is a structured representation of objects and their spatio-temporal relationships in dynamic scenes. Scene Graph Anticipation (SGA) involves predicting future scene g…
3D-MoRe: Unified Modal-Contextual Reasoning for Embodied Question Answering
Rongtao Xu, Han Gao, Mingming Yu +6
With the growing need for diverse and scalable data in indoor scene tasks, such as question answering and dense captioning, we propose 3D-MoRe, a novel paradigm designed to generat…
Dark-EvGS: Event Camera as an Eye for Radiance Field in the Dark
Jingqian Wu, Peiqi Duan, Zongqiang Wang +3
In low-light environments, conventional cameras often struggle to capture clear multi-view images of objects due to dynamic range limitations and motion blur caused by long exposur…
SAMamba: Adaptive State Space Modeling with Hierarchical Vision for Infrared Small Target Detection
Wenhao Xu, Shuchen Zheng, Changwei Wang +4
Infrared small target detection (ISTD) is vital for long-range surveillance in military, maritime, and early warning applications. ISTD is challenged by targets occupying less than…
FDBPL: Faster Distillation-Based Prompt Learning for Region-Aware Vision-Language Models Adaptation
Zherui Zhang, Jiaxin Wu, Changwei Wang +6
Prompt learning as a parameter-efficient method that has been widely adopted to adapt Vision-Language Models (VLMs) to downstream tasks. While hard-prompt design requires domain ex…
Image Recognition with Online Lightweight Vision Transformer: A Survey
Zherui Zhang, Rongtao Xu, Jie Zhou +8
The Transformer architecture has achieved significant success in natural language processing, motivating its adaptation to computer vision tasks. Unlike convolutional neural networ…
CAE-DFKD: Bridging the Transferability Gap in Data-Free Knowledge Distillation
Zherui Zhang, Changwei Wang, Rongtao Xu +4
Data-Free Knowledge Distillation (DFKD) enables the knowledge transfer from the given pre-trained teacher network to the target student model without access to the real training da…
Focus on Local: Finding Reliable Discriminative Regions for Visual Place Recognition
Changwei Wang, Shunpeng Chen, Yukun Song +11
Visual Place Recognition (VPR) is aimed at predicting the location of a query image by referencing a database of geotagged images. For VPR task, often fewer discriminative local re…
S2A: A Unified Framework for Parameter and Memory Efficient Transfer Learning
Tian Jin, Enjun Du, Changwei Wang +2
Parameter-efficient transfer learning (PETL) aims to reduce the scales of pretrained models for multiple downstream tasks. However, as the models keep scaling up, the memory footpr…
PSTNet: Enhanced Polyp Segmentation with Multi-scale Alignment and Frequency Domain Integration
Wenhao Xu, Rongtao Xu, Changwei Wang +3
Accurate segmentation of colorectal polyps in colonoscopy images is crucial for effective diagnosis and management of colorectal cancer (CRC). However, current deep learning-based…
Generalization Boosted Adapter for Open-Vocabulary Segmentation
Wenhao Xu, Changwei Wang, Xuxiang Feng +5
Vision-language models (VLMs) have demonstrated remarkable open-vocabulary object recognition capabilities, motivating their adaptation for dense prediction tasks like segmentation…
HCF-Net: Hierarchical Context Fusion Network for Infrared Small Object Detection
Shibiao Xu, ShuChen Zheng, Wenhao Xu +6
Infrared small object detection is an important computer vision task involving the recognition and localization of tiny objects in infrared images, which usually contain only a few…
Local Feature Matching Using Deep Learning: A Survey
Shibiao Xu, Shunpeng Chen, Rongtao Xu +3
Local feature matching enjoys wide-ranging applications in the realm of computer vision, encompassing domains such as image retrieval, 3D reconstruction, and object recognition. Ho…
Spectral Prompt Tuning:Unveiling Unseen Classes for Zero-Shot Semantic Segmentation
Wenhao Xu, Rongtao Xu, Changwei Wang +4
Recently, CLIP has found practical utility in the domain of pixel-level zero-shot segmentation tasks. The present landscape features two-stage methodologies beset by issues such as…
Segment Anything Model is a Good Teacher for Local Feature Learning
Jingqian Wu, Rongtao Xu, Zach Wood-Doughty +3
Local feature detection and description play an important role in many computer vision tasks, which are designed to detect and describe keypoints in "any scene" and "any downstream…
Self Correspondence Distillation for End-to-End Weakly-Supervised Semantic Segmentation
Rongtao Xu, Changwei Wang, Jiaxi Sun +3
Efficiently training accurate deep models for weakly supervised semantic segmentation (WSSS) with image-level labels is challenging and important. Recently, end-to-end WSSS methods…
MTLDesc: Looking Wider to Describe Better
Changwei Wang, Rongtao Xu, Yuyang Zhang +4
Limited by the locality of convolutional neural networks, most existing local features description methods only learn local descriptors with local information and lack awareness of…