Many matrices associated with fast transforms posess a certain low-rank
...
We propose SeedAL, a method to seed active learning for efficient annota...
Learning models on one labeled dataset that generalize well on another d...
Casting semantic segmentation of outdoor LiDAR point clouds as a 2D prob...
Semantic segmentation of point clouds in autonomous driving datasets req...
Recent advances in self-supervised visual representation learning have p...
We propose a new self-supervised method for pre-training the backbone of...
Predictive performance of machine learning models trained with empirical...
A major paradigm for learning image representations in a self-supervised...
Segmenting or detecting objects in sparse Lidar point clouds are two
imp...
There has been recently a growing interest for implicit shape
representa...
We present FacialFilmroll, a solution for spatially and temporally
consi...
Rigid registration of point clouds with partial overlaps is a longstandi...
Localizing objects in image collections without supervision can help to ...
While there has been a number of studies on Zero-Shot Learning (ZSL) for...
Learning image representations without human supervision is an important...
We propose and study a method called FLOT that estimates scene flow on p...
Face age editing has become a crucial task in film post-production, and ...
We address the problem of style transfer between two photos and propose ...
Recent state-of-the-art methods for point cloud semantic segmentation ar...
We consider the problem of identifying people on the basis of their walk...
We propose a new flexible deep convolutional neural network (convnet) to...
This paper deals with the unification of local and non-local signal
proc...
Spectral clustering has become a popular technique due to its high
perfo...
We study the problem of sampling k-bandlimited signals on graphs. We pro...
Mining useful clusters from high dimensional data has received significa...
We propose a novel method to accurately reconstruct a set of images
repr...