World models, especially in autonomous driving, are trending and drawing...
Bike sharing is emerging globally as an active, convenient, and sustaina...
Representing and synthesizing novel views in real-world dynamic scenes f...
In recent years, vision-centric perception has flourished in various
aut...
We release a new codebase version of the BEVDet, dubbed branch dev2.0. W...
For bike sharing systems, demand prediction is crucial to ensure the tim...
Convolutional neural network (CNN) models have seen advanced improvement...
3D object detection with surrounding cameras has been a promising direct...
Self-supervised monocular methods can efficiently learn depth informatio...
Self-supervised monocular depth estimation is an attractive solution tha...
Deep supervision, or known as 'intermediate supervision' or 'auxiliary
s...
In this paper, we present BEVerse, a unified framework for 3D perception...
Gait benchmarks empower the research community to train and evaluate
hig...
Face benchmarks empower the research community to train and evaluate
hig...
Learning-based Multi-View Stereo (MVS) methods warp source images into t...
Autonomous driving requires accurate and detailed Bird's Eye View (BEV)
...
Depth estimation from images serves as the fundamental step of 3D percep...
Single frame data contains finite information which limits the performan...
Bike sharing is an increasingly popular part of urban transportation sys...
Dataset condensation aims at reducing the network training effort throug...
Autonomous driving perceives the surrounding environment for decision ma...
Dynamic demand prediction is crucial for the efficient operation and
man...
Recent progress has shown that large-scale pre-training using contrastiv...
Our team are developing a new online test that analyses hand movement
fe...
Recently, face recognition in the wild has achieved remarkable success a...
According to WHO statistics, there are more than 204,617,027 confirmed
C...
Retrieval is a crucial stage in web search that identifies a small set o...
The practical application requests both accuracy and efficiency on
multi...
Face clustering is a promising method for annotating unlabeled face imag...
In this paper, we contribute a new million-scale face benchmark containi...
Both appearance cue and constraint cue are important in human pose
estim...
Recently, the leading performance of human pose estimation is dominated ...
Human pose estimation are of importance for visual understanding tasks s...
Convolutional neural networks (CNN) based tracking approaches have shown...
Scale variation remains a challenge problem for object detection. Common...
Both accuracy and efficiency are significant for pose estimation and tra...
Multi-target Multi-camera Tracking (MTMCT) aims to extract the trajector...
Human pose estimation has witnessed a significant advance thanks to the
...
Person re-identification (ReID) has achieved significant improvement und...
Existing methods in video action recognition mostly do not distinguish h...
This paper studies panoptic segmentation, a recently proposed task which...
In order to mitigate the long processing delay and high energy consumpti...
Estimating post-click conversion rate (CVR) accurately is crucial for ra...
Convolutional neural networks (CNN) based tracking approaches have shown...
To date, there have been massive Semi-Structured Documents (SSDs) during...