115 citations · 143 across the 25 of their papers we have counts for
25 papers · 1 filter
A Super-pixel-based Approach to the Stable Interpretation of Neural Networks
Shizhan Gong, Jingwei Zhang, Qi Dou +1
Saliency maps are widely used in the computer vision community for interpreting neural network classifiers. However, due to the randomness of training samples and optimization algo…
Enhanced Scale-aware Depth Estimation for Monocular Endoscopic Scenes with Geometric Modeling
Ruofeng Wei, Bin Li, Kai Chen +3
Scale-aware monocular depth estimation poses a significant challenge in computer-aided endoscopic navigation. However, existing depth estimation methods that do not consider the ge…
Weakly-supervised Medical Image Segmentation with Gaze Annotations
Yuan Zhong, Chenhui Tang, Yumeng Yang +6
Eye gaze that reveals human observational patterns has increasingly been incorporated into solutions for vision tasks. Despite recent explorations on leveraging gaze to aid deep ne…
Holistic-Motion2D: Scalable Whole-body Human Motion Generation in 2D Space
Yuan Wang, Zhao Wang, Junhao Gong +8
In this paper, we introduce a novel path to human motion generation by focusing on 2D space. Traditional methods have primarily generated human motions in 3D, wh…
Structured Gradient-based Interpretations via Norm-Regularized Adversarial Training
Shizhan Gong, Qi Dou, Farzan Farnia
Gradient-based saliency maps have been widely used to explain the decisions of deep neural network classifiers. However, standard gradient-based interpretation maps, including the…
EndoGSLAM: Real-Time Dense Reconstruction and Tracking in Endoscopic Surgeries using Gaussian Splatting
Kailing Wang, Chen Yang, Yuehao Wang +5
Precise camera tracking, high-fidelity 3D tissue reconstruction, and real-time online visualization are critical for intrabody medical imaging devices such as endoscopes and capsul…