230 citations · 291 across the 8 of their papers we have counts for
8 papers
XPos3R: Cross-Modal Transformer for Intraoperative 2D/3D Registration
Shiyan Su, Ruyi Zha, Hongdong Li +2
Intraoperative 2D/3D registration, which aligns live X-ray images with preoperative volumes, is essential for image-guided interventions. Previous regression-based methods suffer f…
DiffNR: Diffusion-Enhanced Neural Representation Optimization for Sparse-View 3D Tomographic Reconstruction
Shiyan Su, Ruyi Zha, Danli Shi +2
Neural representations (NRs), such as neural fields and 3D Gaussians, effectively model volumetric data in computed tomography (CT) but suffer from severe artifacts under sparse-vi…
EndoSurf: Neural Surface Reconstruction of Deformable Tissues with Stereo Endoscope Videos
Ruyi Zha, Xuelian Cheng, Hongdong Li +2
Reconstructing soft tissues from stereo endoscope videos is an essential prerequisite for many medical applications. Previous methods struggle to produce high-quality geometry and…
Deep Laparoscopic Stereo Matching with Transformers
Xuelian Cheng, Yiran Zhong, Mehrtash Harandi +3
The self-attention mechanism, successfully employed with the transformer structure is shown promise in many computer vision tasks including image recognition, and object detection.…
Implicit Motion Handling for Video Camouflaged Object Detection
Xuelian Cheng, Huan Xiong, Deng-Ping Fan +4
We propose a new video camouflaged object detection (VCOD) framework that can exploit both short-term dynamics and long-term temporal consistency to detect camouflaged objects from…
Hierarchical Neural Architecture Search for Deep Stereo Matching
Xuelian Cheng, Yiran Zhong, Mehrtash Harandi +5
To reduce the human efforts in neural network design, Neural Architecture Search (NAS) has been applied with remarkable success to various high-level vision tasks such as classific…
Noise-Aware Unsupervised Deep Lidar-Stereo Fusion
Xuelian Cheng, Yiran Zhong, Yuchao Dai +2
In this paper, we present LidarStereoNet, the first unsupervised Lidar-stereo fusion network, which can be trained in an end-to-end manner without the need of ground truth depth ma…
Skeleton based action recognition using translation-scale invariant image mapping and multi-scale deep cnn
Bo Li, Mingyi He, Xuelian Cheng +2
This paper presents an image classification based approach for skeleton-based video action recognition problem. Firstly, A dataset independent translation-scale invariant image map…