Neural Ordinary Differential Equations (NODEs), a framework of continuous-depth neural networks, have been widely applied, showing exceptional efficacy in coping with representative datasets.
In 3D medical image segmentation, small targets segmentation is crucial for diagnosis but still faces challenges.
Two new datasets were proposed for this problem, named AWA2-LTS and ImageNet-LTS.
Recent progress in 3D scene understanding has explored visual grounding (3DVG) to localize a target object through a language description.
Thus, a more faithful caption can be generated only using point clouds during the inference.
To tackle this problem, we propose the CLEVR3D, a large-scale VQA-3D dataset consisting of 171K questions from 8, 771 3D scenes.
Previous studies focus on the "symptoms" directly, as they try to improve the accuracy or detect possible attacks by adding extra steps to conventional FL models.
It can generalize well on the real-world data from all the other unseen views.
In this report, the technical details of our submission to the EPIC-Kitchens Action Anticipation Challenge 2021 are given.
Based on the grouping results, PFA conducts an FL process in a group-wise way on the federated model to accomplish the adaptation.
This paper aims to improve the transfer performance from another angle - in addition to tuning the weights, we tune the structure of pre-trained models, in order to better match the target task.
Neural Ordinary Differential Equations (NODEs), a framework of continuous-depth neural networks, have been widely applied, showing exceptional efficacy in coping with some representative datasets.
In this paper, we present FW-Net, an end-to-end and real-time deep learning framework for endovascular intervention.
To facilitate future research, we have publicly released all the well-labelled COVID-19 themed apps (and malware) to the research community.
Cryptography and Security
In order to understand the impact of adversarial attacks on depth estimation, we first define a taxonomy of different attack scenarios for depth estimation, including non-targeted attacks, targeted attacks and universal attacks.
Artificial Intelligence (AI) is gradually changing the practice of surgery with the advanced technological development of imaging, navigation and robotic intervention.
Yet, robotic vision poses unique challenges for applying visual algorithms developed from these standard computer vision datasets due to their implicit assumption over non-varying distributions for a fixed set of tasks.
Railway transportation is the artery of China's national economy and plays an important role in the development of today's society.
In this paper, we propose a novel method for highly efficient follicular segmentation of thyroid cytopathological WSIs.
Motion behaviors of a rigid body can be characterized by a 6-dimensional motion trajectory, which contains position vectors of a reference point on the rigid body and rotations of this rigid body over time.