Multi-modal fusion is increasingly being used for autonomous driving tas...
Optical Music Recognition (OMR) is an important technology in music and ...
Multi-agent embodied tasks have recently been studied in complex indoor
...
An innovative sort of mobility platform that can both drive and fly is t...
Noise has always been nonnegligible trouble in object detection by creat...
In this paper, a novel robotic grasping system is established to
automat...
Synthesizing high-fidelity videos from real-world multi-view input is
ch...
This paper introduces a structure-deformable land-air robot which posses...
Single locomotion robots often struggle to adapt in highly variable or
u...
Embodied agents are expected to perform more complicated tasks in an
int...
3D Multi-object tracking (MOT) ensures consistency during continuous dyn...
Amphibious ground-aerial vehicles fuse flying and driving modes to enabl...
The ability to handle objects in cluttered environment has been long
ant...
Keypoint detection and description play a central role in computer visio...
Learning multiple tasks sequentially without forgetting previous knowled...
Building a deep learning model for a Question-Answering (QA) task requir...
In the Vision-and-Language Navigation task, the embodied agent follows
l...
We present TWIST, a novel self-supervised representation learning method...
Referring expressions are commonly used when referring to a specific tar...
In visual semantic navigation, the robot navigates to a target object wi...
In this paper, we propose a novel Knowledge-based Embodied Question Answ...
There has recently been growing interest in utilizing multimodal sensors...
Model Predictive Control (MPC) has shown the great performance of target...
Unsupervised contrastive learning has achieved outstanding success, whil...
Robots have limited adaptation ability compared to humans and animals in...
Deep reinforcement learning has made significant progress in robotic
man...
Embodiment is an important characteristic for all intelligent agents
(cr...
This paper considers crowded massive multiple input multiple output (MIM...
Action repetition counting is to estimate the occurrence times of the
re...
In this paper,we propose a novel task of Manipulation Question
Answering...
This paper introduces a new type of system for fabric defect detection w...
In this paper, we study Reinforcement Learning from Demonstrations (RLfD...
This paper studies Learning from Observations (LfO) for imitation learni...
Detecting actions in videos is an important yet challenging task. Previo...
Pose prediction is to predict future poses given a window of previous po...
We present FoveaBox, an accurate, flexible and completely anchor-free
fr...
We present consistent optimization for single stage object detection.
Pr...
State-of-the-art object detectors usually learn multi-scale representati...
Learning and inference movement is a very challenging problem due to its...
Task transfer is extremely important for reinforcement learning, since i...
We present RON, an efficient and effective framework for generic object
...