This work proposes an end-to-end multi-camera 3D multi-object tracking (...
The goal of autonomous vehicles is to navigate public roads safely and
c...
The imitation learning of self-driving vehicle policies through behavior...
We present a new method that views object detection as a direct set
pred...
Since DeepMind's AlphaZero, Zero learning quickly became the state-of-th...
In this paper, we address the problem of visually guided rearrangement
p...
We propose to impose symmetry in neural network parameters to improve
pa...
We propose to impose symmetry in neural network parameters to improve
pa...
We study the first-order scattering transform as a candidate for reducin...
Scattering networks are a class of designed Convolutional Neural Network...
Deep neural networks with skip-connections, such as ResNet, show excelle...
We use the scattering network as a generic and fixed ini-tialization of ...
Attention plays a critical role in human visual experience. Furthermore,...
Deep residual networks were shown to be able to scale up to thousands of...
The recent COCO object detection dataset presents several new challenges...
In this paper we show how to learn directly from image data (i.e., witho...