Dense SLAM based on monocular cameras does indeed have immense applicati...
Different from traditional video cameras, event cameras capture asynchro...
Light-weight time-of-flight (ToF) depth sensors are compact and
cost-eff...
This paper tackles the challenge of creating relightable and animatable
...
Recently, Neural Radiance Fields (NeRF) has exhibited significant succes...
Recently, the editing of neural radiance fields (NeRFs) has gained
consi...
We present a novel method for recovering the absolute pose and shape of ...
A fully automated object reconstruction pipeline is crucial for digital
...
This paper introduces a novel representation of volumetric videos for
re...
Despite the great success in 2D editing using user-friendly tools, such ...
Performing accurate localization while maintaining the low-level
communi...
Event cameras provide high temporal precision, low data rates, and high
...
Local feature matching aims at establishing sparse correspondences betwe...
We present a novel approach to interactive 3D object perception for robo...
This paper addresses the challenge of quickly reconstructing free-viewpo...
Structure-from-Motion is a technology used to obtain scene structure thr...
We propose a new method for object pose estimation without CAD models. T...
Feature matching is an essential step in visual localization, where the
...
We present intrinsic neural radiance fields, dubbed IntrinsicNeRF, that
...
Data workers use various scripting languages for data transformation, su...
Light-weight time-of-flight (ToF) depth sensors are small, cheap, low-en...
Virtual content creation and interaction play an important role in moder...
Very recently neural implicit rendering techniques have been rapidly evo...
Expanding an existing tourist photo from a partially captured scene to a...
In this paper, we propose a tightly-coupled SLAM system fused with RGB,
...
This paper addresses the challenge of reconstructing 3D indoor scenes fr...
We, as human beings, can understand and picture a familiar scene from
ar...
Convolutional Neural Network (CNN), which mimics human visual perception...
We propose a novel method to reconstruct the 3D shapes of transparent ob...
This paper aims to reconstruct an animatable human model from a video of...
Video Panoptic Segmentation (VPS) requires generating consistent panopti...
We propose SelfRecon, a clothed human body reconstruction method that
co...
This paper aims to reduce the rendering time of generalizable radiance
f...
3D representation and reconstruction of human bodies have been studied f...
In this paper, we take the advantage of previous pre-trained models (PTM...
Implicit neural rendering techniques have shown promising results for no...
Visual localization is of great importance in robotics and computer visi...
This paper addresses the challenge of reconstructing an animatable human...
In this paper, we propose StereoPIFu, which integrates the geometric
con...
We present a novel framework named NeuralRecon for real-time 3D scene
re...
We present a novel method for local image feature matching. Instead of
p...
In this paper, we introduce the new task of reconstructing 3D human pose...
Generating high-fidelity talking head video by fitting with the input au...
This paper proposes a novel active boundary loss for semantic segmentati...
We propose a novel deep generative model based on causal convolutions fo...
Most commercially available optical see-through head-mounted displays
(O...
This paper addresses the challenge of novel view synthesis for a human
p...
This paper proposes a novel location-aware deep learning-based single im...
Learning non-rigid registration in an end-to-end manner is challenging d...
Recent learning-based LiDAR odometry methods have demonstrated their
com...