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