9 accepted papers
Large Language Models (LLMs) have significantly advanced code analysis tasks, yet they struggle to detect malicious behaviors fragmented across files, whose intricate dependencies easily get lost in the vast amount of benign code. We therefore propose a graph-centric attention acquisition pipeline t…
With the growing accessibility of large-scale 3D point clouds from LiDAR and photogrammetric techniques, 3D change detection (3DCD) has become essential for understanding dynamic scenes. Existing methods typically formulate this as segmentation, treating each point independently for binary classific
Delineation of prostate cancer (PCa) on ultrasound images has become an essential technique for early PCa treatment, which still faces several challenges, such as low image contrast and blurred organ boundaries. Facing the aforementioned issues, a novel coarse-fine segmentation framework method is a…
"RGB-Thermal (RGB-T) semantic segmentation is an important research branch of multi-modal image segmentation. The current RGB-T semantic segmentation methods generally have two unsolved and typical shortcomings. First, they do not have the open-vocabulary recognition ability, which significantly lim…
High-fidelity garment reconstruction is essential for various applications such as garment design and virtual try-on. While image-based reconstruction methods have made significant progress with deep generative models, generating 3D models from hand-drawn sketches to meet design intentions remains c…
Learning to capture human motion is essential to 3D human pose and shape estimation from monocular video, which is widely used in many 3D applications. However, the existing methods mainly rely on recurrent or convolutional operation to model such temporal information, which limits the ability to ca…
With the growing trend of virtual try-on, multi-pose tasks attract researchers due to their higher commercial value. Prior methods lack an effective geometric deformation to maintain the original image details resulting in many details loss in the head and garment. To address this problem, we propos…
3D virtual try-on receives widespread attention from scholars due to its great practical and commercial values. In prior methods, the fundamental problems lie in the limitations on texture retention during garment deformation and the lack of feature context capture during depth estimation. To addres…
Image-based virtual try-on systems with the goal of transferring a target clothing item onto the corresponding region of a person have received great attention recently. However, it is still a challenge for the existing methods to generate photo-realistic try-on images while preserving non-target de…