3D object-level mapping is a fundamental problem in robotics, which is
e...
6D pose estimation of textureless shiny objects has become an essential
...
For learning-based sound event localization and detection (SELD) methods...
The physical design process of large-scale designs is a time-consuming t...
To achieve high-accuracy manipulation in the presence of unknown dynamic...
Image inverse halftoning is a classic image restoration task, aiming to
...
Among the great successes of Reinforcement Learning (RL), self-play
algo...
Reconfigurable intelligent surface (RIS) is a new technique that is able...
Equipped with the trained environmental dynamics, model-based offline
re...
The Outstanding performance and growing size of Large Language Models ha...
Robotic eye-in-hand calibration is the task of determining the rigid 6-D...
RGB-D semantic segmentation can be advanced with convolutional neural
ne...
This paper studies the exploitation of triple polarization (TP) for
mult...
Human data labeling is an important and expensive task at the heart of
s...
In recent years, arbitrary image style transfer has attracted more and m...
This paper investigates the utilization of triple polarization (TP) for
...
6D pose estimation of textureless objects is a valuable but challenging ...
The current fusion positioning systems are mainly based on filtering
alg...
This paper proposes DisCo, an automatic deep learning compilation module...
Sound event localization and detection (SELD) is a joint task of sound e...
Tuning of stochastic gradient algorithms (SGAs) for optimization and sam...
Automated Program Repair (APR) techniques have drawn wide attention from...
High dimensional distributions, especially those with heavy tails, are
n...
Maintaining an up-to-date map to reflect recent changes in the scene is ...
To train modern large DNN models, pipeline parallelism has recently emer...
Polyphonic sound event localization and detection (SELD) aims at detecti...
Depth acquisition with the active stereo camera is a challenging task fo...
A powerful way to understand a complex query is by observing how it oper...
Multi-agent reinforcement learning (MARL) has received increasing attent...
With breakthrough of AlphaGo, AI in human-computer game has become a ver...
Deepfake poses a serious threat to the reliability of judicial evidence ...
On modern x86 processors, data prefetching instructions can be used by
p...
Offline reinforcement learning (RL) shows promise of applying RL to
real...
Recently, neural network compression schemes like channel pruning have b...
Most of reinforcement learning algorithms optimize the discounted criter...
Learning from datasets without interaction with environments (Offline
Le...
Despite superior performance on various natural language processing task...
Though network sparsity emerges as a promising direction to overcome the...
This paper proposes a dual-stage, low complexity, and reconfigurable
tec...
Yang et al. (2016) proved that the symmetric random walk Metropolis–Hast...
In robotic bin-picking applications, the perception of texture-less, hig...
This paper considers enumerating answers to similarity-join queries unde...
Recently, end-to-end (E2E) speech recognition has become popular, since ...
We consider a class of queries called durability prediction queries that...
The reliable fusion of depth maps from multiple viewpoints has become an...
Many recent machine learning models show dynamic shape characteristics.
...
A way of finding interesting or exceptional records from instant-stamped...
From ancient to modern times, acoustic structures have been used to cont...
The literature has witnessed the success of applying deep Transfer Learn...
The intensive computation of Automatic Speech Recognition (ASR) models
o...