Learning to predict reliable characteristic orientations of 3D point clo...
In this paper, we propose binary radiance fields (BiRF), a storage-effic...
Despite the increasing popularity of LiDAR sensors, perception algorithm...
We propose LaplacianFusion, a novel approach that reconstructs detailed ...
Designing a neural network architecture for molecular representation is
...
We address the problem of generating a sequence of LEGO brick assembly w...
We present a novel method of learning style-agnostic representation usin...
Recent 3D registration methods can effectively handle large-scale or
par...
Neural networks are prone to be biased towards spurious correlations bet...
We present a rotated hyperbolic wrapped normal distribution (RoWN), a si...
Assembling parts into an object is a combinatorial problem that arises i...
The recent success of neural networks enables a better interpretation of...
Spinning LiDAR data are prevalent for 3D perception tasks, yet its
cylin...
3D neural networks have become prevalent for many 3D vision tasks includ...
In this paper, we introduce a new dataset, named InstaOrder, that can be...
Point cloud obtained from 3D scanning is often sparse, noisy, and irregu...
MLP-Mixer has newly appeared as a new challenger against the realm of CN...
Videos are a popular media form, where online video streaming has recent...
Conditional Generative Adversarial Networks (cGAN) generate realistic im...
Discovering a solution in a combinatorial space is prevalent in many
rea...
This paper presents a new large multiview dataset called HUMBI for human...
Point cloud registration is the task of estimating the rigid transformat...
In this work, we propose a camera self-calibration algorithm for generic...
Recent conditional image synthesis approaches provide high-quality
synth...
This paper presents an effective method for generating a spatiotemporal
...
We propose deep virtual markers, a framework for estimating dense and
ac...
Conditional image synthesis is the task to generate high-fidelity divers...
Many problems in science and engineering can be formulated in terms of
g...
3D shape generation has drawn attention in computer vision and machine
l...
We present an approach to predict future video frames given a sequence o...
This paper presents a new dataset called HUMBI - a large corpus of high
...
We present an approach to semantic scene analysis using deep convolution...
Open3D is an open-source library that supports rapid development of soft...
We propose a method to refine geometry of 3D meshes from a consumer leve...