activity
20232026
most citedRefDrone: A Challenging Benchmark for Referring Expression Comprehension in Drone Scenes

1 citations · 1 across the 14 of their papers we have counts for

collaborators

16 papers

cs.CV2026

IVC-Prune: Revealing the Implicit Visual Coordinates in LVLMs for Vision Token Pruning

Zhichao Sun, Yidong Ma, Gang Liu +4

Large Vision-Language Models (LVLMs) achieve impressive performance across multiple tasks. A significant challenge, however, is their prohibitive inference cost when processing hig…

cs.CV2026

From Pairs to Sequences: Track-Aware Policy Gradients for Keypoint Detection

Yepeng Liu, Hao Li, Liwen Yang +8

Keypoint-based matching is a fundamental component of modern 3D vision systems, such as Structure-from-Motion (SfM) and SLAM. Most existing learning-based methods are trained on im…

cs.CV2025

LiftFeat: 3D Geometry-Aware Local Feature Matching

Yepeng Liu, Wenpeng Lai, Zhou Zhao +4

Robust and efficient local feature matching plays a crucial role in applications such as SLAM and visual localization for robotics. Despite great progress, it is still very challen…

cs.CV2025

Consistent-Point: Consistent Pseudo-Points for Semi-Supervised Crowd Counting and Localization

Yuda Zou, Zelong Liu, Yuliang Gu +2

Crowd counting and localization are important in applications such as public security and traffic management. Existing methods have achieved impressive results thanks to extensive…

cs.CV2025

CQ-DINO: Mitigating Gradient Dilution via Category Queries for Vast Vocabulary Object Detection

Zhichao Sun, Huazhang Hu, Yidong Ma +5

With the exponential growth of data, traditional object detection methods are increasingly struggling to handle vast vocabulary object detection tasks effectively. We analyze two k…

cs.CV2025★ 1 cited

RefDrone: A Challenging Benchmark for Referring Expression Comprehension in Drone Scenes

Zhichao Sun, Yepeng Liu, Zhiling Su +7

Drones have become prevalent robotic platforms with diverse applications, showing significant potential in Embodied Artificial Intelligence (Embodied AI). Referring Expression Comp…

cs.CV2025

MIFNet: Learning Modality-Invariant Features for Generalizable Multimodal Image Matching

Yepeng Liu, Zhichao Sun, Baosheng Yu +4

Many keypoint detection and description methods have been proposed for image matching or registration. While these methods demonstrate promising performance for single-modality ima…

cs.CV2024

Shape Transformation Driven by Active Contour for Class-Imbalanced Semi-Supervised Medical Image Segmentation

Yuliang Gu, Yepeng Liu, Zhichao Sun +3

Annotating 3D medical images demands expert knowledge and is time-consuming. As a result, semi-supervised learning (SSL) approaches have gained significant interest in 3D medical i…

cs.CV2024

Progressive Retinal Image Registration via Global and Local Deformable Transformations

Yepeng Liu, Baosheng Yu, Tian Chen +4

Retinal image registration plays an important role in the ophthalmological diagnosis process. Since there exist variances in viewing angles and anatomical structures across differe…

eess.IV2024

Shape-intensity knowledge distillation for robust medical image segmentation

Wenhui Dong, Bo Du, Yongchao Xu

Many medical image segmentation methods have achieved impressive results. Yet, most existing methods do not take into account the shape-intensity prior information. This may lead t…

cs.CV2024

Prompting Segment Anything Model with Domain-Adaptive Prototype for Generalizable Medical Image Segmentation

Zhikai Wei, Wenhui Dong, Peilin Zhou +3

Deep learning based methods often suffer from performance degradation caused by domain shift. In recent years, many sophisticated network structures have been designed to tackle th…

cs.CV2024

Position-Guided Prompt Learning for Anomaly Detection in Chest X-Rays

Zhichao Sun, Yuliang Gu, Yepeng Liu +3

Anomaly detection in chest X-rays is a critical task. Most methods mainly model the distribution of normal images, and then regard significant deviation from normal distribution as…

eess.IV2024

Spatial-aware Attention Generative Adversarial Network for Semi-supervised Anomaly Detection in Medical Image

Zerui Zhang, Zhichao Sun, Zelong Liu +4

Medical anomaly detection is a critical research area aimed at recognizing abnormal images to aid in diagnosis.Most existing methods adopt synthetic anomalies and image restoration…

eess.IV2024

MoreStyle: Relax Low-frequency Constraint of Fourier-based Image Reconstruction in Generalizable Medical Image Segmentation

Haoyu Zhao, Wenhui Dong, Rui Yu +3

The task of single-source domain generalization (SDG) in medical image segmentation is crucial due to frequent domain shifts in clinical image datasets. To address the challenge of…

eess.IV2024

WIA-LD2ND: Wavelet-based Image Alignment for Self-supervised Low-Dose CT Denoising

Haoyu Zhao, Yuliang Gu, Zhou Zhao +3

In clinical examinations and diagnoses, low-dose computed tomography (LDCT) is crucial for minimizing health risks compared with normal-dose computed tomography (NDCT). However, re…

cs.CV2023

Shifted Autoencoders for Point Annotation Restoration in Object Counting

Yuda Zou, Xin Xiao, Peilin Zhou +3

Object counting typically uses 2D point annotations. The complexity of object shapes and the subjectivity of annotators may lead to annotation inconsistency, potentially confusing…