The rapid growth of memory and computation requirements of large languag...
Current diffusion-based image restoration methods feed degraded input im...
Experimentation on real robots is demanding in terms of time and costs. ...
The Contrastive Language-Image Pre-training (CLIP) has recently shown
re...
This paper proposes a technique for efficiently modeling dynamic humans ...
The ability to detect slip, particularly incipient slip, enables robotic...
Due to effective pattern mining and feature representation, neural
forec...
3D multi-object tracking (MOT) is vital for many applications including
...
This paper introduces a novel transformer-based network architecture,
Fl...
Creative sketch is a universal way of visual expression, but translating...
The social robot navigation is an open and challenging problem. In exist...
Neural machine translation (NMT) has achieved remarkable success in prod...
Value-decomposition methods, which reduce the difficulty of a multi-agen...
This report introduces our winning solution of the real-robot phase of t...
This paper studies the problem of learning a control policy without the ...
Simulation is essential to validate autonomous driving systems. However,...
This paper describes the submission of the RoyalFlush neural machine
tra...
Existing learning-based multi-view stereo (MVS) methods rely on the dept...
In this work, we empirically confirm that non-autoregressive translation...
End-to-end reinforcement learning techniques are among the most successf...
K-Nearest Neighbor Neural Machine Translation (kNN-MT) successfully
inco...
The panorama image can simultaneously demonstrate complete information o...
Load balancing (LB) is a challenging issue in the hybrid light fidelity
...
Temporal action segmentation (TAS) aims to classify and locate actions i...
Recent advanced studies have spent considerable human efforts on optimiz...
In the past decade, object detection tasks are defined mostly by large p...
In this paper we introduce SiamMask, a framework to perform both visual
...
Human action recognition is a quite hugely investigated area where most
...
The well-developed ETS (ExponenTial Smoothing or Error, Trend, Seasonali...
This paper describes a deep reinforcement learning (DRL) approach that w...
We introduce Optical Flow TransFormer (FlowFormer), a transformer-based
...
Unsupervised point cloud completion aims at estimating the corresponding...
Temporal representation is the cornerstone of modern action detection
te...
Cross-modality interaction is a critical component in Text-Video Retriev...
Autofluorescence lifetime images reveal unique characteristics of endoge...
In this paper we obtain further improvement of index bounds for characte...
The Visual Domain Adaptation (VisDA) 2021 Challenge calls for unsupervis...
Deep neural networks (DNNs) have achieved great success in the area of
c...
Providing safety guarantees for Autonomous Vehicle (AV) systems with
mac...
General Continual Learning (GCL) aims at learning from non independent a...
Image-based geometric modeling and novel view synthesis based on sparse,...
Software vulnerabilities are usually caused by design flaws or implement...
Recent works have shown that convolutional networks have substantially
i...
Energy conservation of large data centers for high-performance computing...
We design and experimentally evaluate a hybrid safe-by-construction coll...
We propose a novel feature re-identification method for real-time
visual...
Nowadays, live-stream and short video shopping in E-commerce have grown
...
Unmanned Aerial Vehicle (UAV) offers lots of applications in both commer...
Traditional neural machine translation is limited to the topmost encoder...
The standard neural machine translation model can only decode with the s...