We propose a novel framework to automatically learn to aggregate and
tra...
We present a novel method for reconstructing clothed humans from a spars...
Reconstructing neural radiance fields with explicit volumetric
represent...
Panoramic image enables deeper understanding and more holistic perceptio...
We propose a method to learn a high-quality implicit 3D head avatar from...
We study the problem of estimating optical flow from event cameras. One
...
Deep convolutional neural network (DCNN for short) models are vulnerable...
There is an emerging trend of using neural implicit functions for map
re...
This paper proposes a deep recurrent Rotation Averaging Graph Optimizer
...
This paper presents an end-to-end neural mapping method for camera
local...
We present an explicit-grid based method for efficiently reconstructing
...
Hand, the bearer of human productivity and intelligence, is receiving mu...
Visual relocalization has been a widely discussed problem in 3D vision: ...
Estimating the 6D pose for unseen objects is in great demand for many
re...
Due to the increasing demand in films and games, synthesizing 3D avatar
...
3D motion estimation including scene flow and point cloud registration h...
Neural fields such as implicit surfaces have recently enabled avatar mod...
We present a dataset of 371 3D models of everyday tabletop objects along...
Estimating the accurate depth from a single image is challenging since i...
We propose VoLux-GAN, a generative framework to synthesize 3D-aware face...
Transformers have been successful in many vision tasks, thanks to their
...
Spotting graphical symbols from the computer-aided design (CAD) drawings...
State-of-the-art face recognition methods typically take the
multi-class...
Access to large and diverse computer-aided design (CAD) drawings is crit...
Modern deep-learning-based lane detection methods are successful in most...
In this paper, we propose a cloud-based benchmark for robotic grasping a...
This paper presents a method for riggable 3D face reconstruction from
mo...
Camera localization aims to estimate 6 DoF camera poses from RGB images....
In this paper, we address the problem of building dense correspondences
...
Augmented reality (AR) has gained increasingly attention from both resea...
Accurate localization is fundamental to a variety of applications, such ...
We present a novel framework to learn to convert the perpixel photometri...
There are increasing interests of studying the structure-from-motion (Sf...
The integration of multiple cameras and 3D Li- DARs has become basic
con...
Unsupervised person re-identification (re-ID) attractsincreasing attenti...
Deep learning based 3D shape generation methods generally utilize latent...
This paper proposes a knowledge distillation method for foreground objec...
Previous methods on estimating detailed human depth often require superv...
We study the energy minimization problem in low-level vision tasks from ...
In this work, we propose an end-to-end framework to learn local multi-vi...
Convolutional Neural Networks (CNNs) are typically constructed by stacki...
This paper studies a new problem, namely active lighting recurrence (ALR...
We present a method to capture both 3D shape and spatially varying
refle...
The deep multi-view stereo (MVS) and stereo matching approaches generall...
We present an unsupervised approach for factorizing object appearance in...
This paper presents a neural network to estimate a detailed depth map of...
Dense depth perception is critical for autonomous driving and other robo...
360 video provides an immersive experience for viewers, allowing them
to...
This paper presents a new training mechanism called Batch Feature Erasin...
This paper introduces a neural network to solve the structure-from-motio...