research
∙
01/29/2023
Producing Usable Taxonomies Cheaply and Rapidly at Pinterest Using Discovered Dynamic μ-Topics
Creating a taxonomy of interests is expensive and human-effort intensive...
share
research
∙
01/18/2023
Joint Representation Learning for Text and 3D Point Cloud
Recent advancements in vision-language pre-training (e.g. CLIP) have sho...
research
∙
11/27/2022
A Faster, Lighter and Stronger Deep Learning-Based Approach for Place Recognition
Visual Place Recognition is an essential component of systems for camera...
research
∙
11/17/2022
Cross-Modal Adapter for Text-Video Retrieval
Text-video retrieval is an important multi-modal learning task, where th...
research
∙
10/12/2022
Efficient Knowledge Distillation from Model Checkpoints
Knowledge distillation is an effective approach to learn compact models ...
research
∙
07/26/2022
RenderNet: Visual Relocalization Using Virtual Viewpoints in Large-Scale Indoor Environments
Visual relocalization has been a widely discussed problem in 3D vision: ...
research
∙
07/19/2022
Deep Semantic Statistics Matching (D2SM) Denoising Network
The ultimate aim of image restoration like denoising is to find an exact...
research
∙
06/13/2022
Exploring Structure-aware Transformer over Interaction Proposals for Human-Object Interaction Detection
Recent high-performing Human-Object Interaction (HOI) detection techniqu...
research
∙
05/23/2022
Learning heterophilious edge to drop: A general framework for boosting graph neural networks
Graph Neural Networks (GNNs) aim at integrating node contents with graph...
research
∙
03/17/2022
Mutual Generative Transformer Learning for Cross-view Geo-localization
Cross-view geo-localization (CVGL), which aims to estimate the geographi...
research
∙
02/14/2022
Domain Adaptation via Prompt Learning
Unsupervised domain adaption (UDA) aims to adapt models learned from a w...
research
∙
12/08/2021
Fully Attentional Network for Semantic Segmentation
Recent non-local self-attention methods have proven to be effective in c...
research
∙
10/27/2021
Denoised Non-Local Neural Network for Semantic Segmentation
The non-local network has become a widely used technique for semantic se...
research
∙
10/01/2021
On the Importance of Gradients for Detecting Distributional Shifts in the Wild
Detecting out-of-distribution (OOD) data has become a critical component...
research
∙
09/18/2021
Domain Composition and Attention for Unseen-Domain Generalizable Medical Image Segmentation
Domain generalizable model is attracting increasing attention in medical...
research
∙
06/29/2021
IMENet: Joint 3D Semantic Scene Completion and 2D Semantic Segmentation through Iterative Mutual Enhancement
3D semantic scene completion and 2D semantic segmentation are two tightl...
research
∙
06/26/2021
Toward Less Hidden Cost of Code Completion with Acceptance and Ranking Models
Code completion is widely used by software developers to provide coding ...
research
∙
05/31/2021
Not All Images are Worth 16x16 Words: Dynamic Vision Transformers with Adaptive Sequence Length
Vision Transformers (ViT) have achieved remarkable success in large-scal...
research
∙
05/05/2021
MOS: Towards Scaling Out-of-distribution Detection for Large Semantic Space
Detecting out-of-distribution (OOD) inputs is a central challenge for sa...
research
∙
04/30/2021
BiCnet-TKS: Learning Efficient Spatial-Temporal Representation for Video Person Re-Identification
In this paper, we present an efficient spatial-temporal representation f...
research
∙
04/05/2021
FocusNetv2: Imbalanced Large and Small Organ Segmentation with Adversarial Shape Constraint for Head and Neck CT Images
Radiotherapy is a treatment where radiation is used to eliminate cancer ...
research
∙
04/02/2021
SDAN: Squared Deformable Alignment Network for Learning Misaligned Optical Zoom
Deep Neural Network (DNN) based super-resolution algorithms have greatly...
research
∙
03/31/2021
Learning Camera Localization via Dense Scene Matching
Camera localization aims to estimate 6 DoF camera poses from RGB images....
research
∙
03/27/2021
AR Mapping: Accurate and Efficient Mapping for Augmented Reality
Augmented reality (AR) has gained increasingly attention from both resea...
research
∙
03/27/2021
Compact 3D Map-Based Monocular Localization Using Semantic Edge Alignment
Accurate localization is fundamental to a variety of applications, such ...
research
∙
03/10/2021
AttaNet: Attention-Augmented Network for Fast and Accurate Scene Parsing
Two factors have proven to be very important to the performance of seman...
research
∙
02/03/2021
Automatic Segmentation of Organs-at-Risk from Head-and-Neck CT using Separable Convolutional Neural Network with Hard-Region-Weighted Loss
Nasopharyngeal Carcinoma (NPC) is a leading form of Head-and-Neck (HAN) ...
research
∙
12/07/2020
Sparse Single Sweep LiDAR Point Cloud Segmentation via Learning Contextual Shape Priors from Scene Completion
LiDAR point cloud analysis is a core task for 3D computer vision, especi...
research
∙
10/11/2020
Glance and Focus: a Dynamic Approach to Reducing Spatial Redundancy in Image Classification
The accuracy of deep convolutional neural networks (CNNs) generally impr...
research
∙
09/28/2020
Concentrated Multi-Grained Multi-Attention Network for Video Based Person Re-Identification
Occlusion is still a severe problem in the video-based Re-IDentification...
research
∙
08/17/2020
Multi-organ Segmentation via Co-training Weight-averaged Models from Few-organ Datasets
Multi-organ segmentation has extensive applications in many clinical app...
research
∙
08/09/2020
Global Optimum Search in Quantum Deep Learning
This paper aims to solve machine learning optimization problem by using ...
research
∙
07/24/2020
An LSTM Approach to Temporal 3D Object Detection in LiDAR Point Clouds
Detecting objects in 3D LiDAR data is a core technology for autonomous d...
research
∙
06/24/2020
Disentangle Perceptual Learning through Online Contrastive Learning
Pursuing realistic results according to human visual perception is the c...
research
∙
03/03/2020
DiPE: Deeper into Photometric Errors for Unsupervised Learning of Depth and Ego-motion from Monocular Videos
Unsupervised learning of depth and ego-motion from unlabelled monocular ...
research
∙
11/19/2019
HighEr-Resolution Network for Image Demosaicing and Enhancing
Neural-networks based image restoration methods tend to use low-resoluti...
research
∙
10/24/2019
Low-Resource Sequence Labeling via Unsupervised Multilingual Contextualized Representations
Previous work on cross-lingual sequence labeling tasks either requires p...
research
∙
07/28/2019
FocusNet: Imbalanced Large and Small Organ Segmentation with an End-to-End Deep Neural Network for Head and Neck CT Images
In this paper, we propose an end-to-end deep neural network for solving ...
research
∙
07/26/2019
Place Clustering-based Feature Recombination for Visual Place Recognition
Visual place recognition is an important problem in both computer vision...
research
∙
03/09/2019
How Effectively Can Indoor Wireless Positioning Relieve Visual Tracking Pains: A Camera-Rao Bound Viewpoint
Visual tracking is fragile in some difficult scenarios, for instance, ap...
research
∙
03/27/2018
ClickBAIT-v2: Training an Object Detector in Real-Time
Modern deep convolutional neural networks (CNNs) for image classificatio...
research
∙
02/09/2018
Multiple Target Tracking by Learning Feature Representation and Distance Metric Jointly
Designing a robust affinity model is the key issue in multiple target tr...
research
∙
05/02/2017
Active Image-based Modeling
We seek to automate the data capturing process in image-based modeling, ...
research
∙
02/03/2015
Recognizing Focal Liver Lesions in Contrast-Enhanced Ultrasound with Discriminatively Trained Spatio-Temporal Model
The aim of this study is to provide an automatic computational framework...
research
∙
02/02/2015