research
∙
07/18/2023
ActionPrompt: Action-Guided 3D Human Pose Estimation With Text and Pose Prompting
Recent 2D-to-3D human pose estimation (HPE) utilizes temporal consistenc...
share
research
∙
06/28/2023
Hybrid Distillation: Connecting Masked Autoencoders with Contrastive Learners
Representation learning has been evolving from traditional supervised tr...
research
∙
04/26/2023
Scene Graph Lossless Compression with Adaptive Prediction for Objects and Relations
The scene graph is a new data structure describing objects and their pai...
research
∙
03/05/2023
Learned Lossless Compression for JPEG via Frequency-Domain Prediction
JPEG images can be further compressed to enhance the storage and transmi...
research
∙
02/15/2023
Pose-Oriented Transformer with Uncertainty-Guided Refinement for 2D-to-3D Human Pose Estimation
There has been a recent surge of interest in introducing transformers to...
research
∙
07/31/2022
SdAE: Self-distillated Masked Autoencoder
With the development of generative-based self-supervised learning (SSL) ...
research
∙
05/31/2022
Hierarchical Spherical CNNs with Lifting-based Adaptive Wavelets for Pooling and Unpooling
Pooling and unpooling are two essential operations in constructing hiera...
research
∙
04/27/2022
LiftPool: Lifting-based Graph Pooling for Hierarchical Graph Representation Learning
Graph pooling has been increasingly considered for graph neural networks...
research
∙
04/25/2022
Hybrid ISTA: Unfolding ISTA With Convergence Guarantees Using Free-Form Deep Neural Networks
It is promising to solve linear inverse problems by unfolding iterative ...
research
∙
11/23/2021
Hierarchical Graph Networks for 3D Human Pose Estimation
Recent 2D-to-3D human pose estimation works tend to utilize the graph st...
research
∙
08/03/2021
Spectral Graph Convolutional Networks With Lifting-based Adaptive Graph Wavelets
Spectral graph convolutional networks (SGCNs) have been attracting incre...
research
∙
07/04/2021
Bag of Instances Aggregation Boosts Self-supervised Learning
Recent advances in self-supervised learning have experienced remarkable ...
research
∙
06/18/2021
Message Passing in Graph Convolution Networks via Adaptive Filter Banks
Graph convolution networks, like message passing graph convolution netwo...
research
∙
06/08/2021
Multi-dataset Pretraining: A Unified Model for Semantic Segmentation
Collecting annotated data for semantic segmentation is time-consuming an...
research
∙
12/07/2020
NCGNN: Node-level Capsule Graph Neural Network
Message passing has evolved as an effective tool for designing Graph Neu...
research
∙
10/19/2020
MimicNorm: Weight Mean and Last BN Layer Mimic the Dynamic of Batch Normalization
Substantial experiments have validated the success of Batch Normalizatio...
research
∙
09/10/2020
Key-Point Sequence Lossless Compression for Intelligent Video Analysis
Feature coding has been recently considered to facilitate intelligent vi...
research
∙
06/19/2020
Graph Pooling with Node Proximity for Hierarchical Representation Learning
Graph neural networks have attracted wide attentions to enable represent...
research
∙
01/09/2020
Spatial-Temporal Transformer Networks for Traffic Flow Forecasting
Traffic forecasting has emerged as a core component of intelligent trans...
research
∙
10/09/2019