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08/08/2023
Prune Spatio-temporal Tokens by Semantic-aware Temporal Accumulation
Transformers have become the primary backbone of the computer vision com...
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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...
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06/28/2023
Hybrid Distillation: Connecting Masked Autoencoders with Contrastive Learners
Representation learning has been evolving from traditional supervised tr...
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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...
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03/08/2023
Dynamic Scenario Representation Learning for Motion Forecasting with Heterogeneous Graph Convolutional Recurrent Networks
Due to the complex and changing interactions in dynamic scenarios, motio...
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03/05/2023
Learned Lossless Compression for JPEG via Frequency-Domain Prediction
JPEG images can be further compressed to enhance the storage and transmi...
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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...
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11/09/2022
MFDNet: Towards Real-time Image Denoising On Mobile Devices
Deep convolutional neural networks have achieved great progress in image...
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10/01/2022
Motion-inductive Self-supervised Object Discovery in Videos
In this paper, we consider the task of unsupervised object discovery in ...
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07/31/2022
SdAE: Self-distillated Masked Autoencoder
With the development of generative-based self-supervised learning (SSL) ...
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07/12/2022
Dual Contrastive Learning for Spatio-temporal Representation
Contrastive learning has shown promising potential in self-supervised sp...
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06/10/2022
Masked Autoencoders are Robust Data Augmentors
Deep neural networks are capable of learning powerful representations to...
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06/06/2022
Optimization-based Block Coordinate Gradient Coding for Mitigating Partial Stragglers in Distributed Learning
Gradient coding schemes effectively mitigate full stragglers in distribu...
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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...
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04/27/2022
LiftPool: Lifting-based Graph Pooling for Hierarchical Graph Representation Learning
Graph pooling has been increasingly considered for graph neural networks...
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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 ...
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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...
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09/18/2021
Optimization-based Block Coordinate Gradient Coding
Existing gradient coding schemes introduce identical redundancy across t...
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08/03/2021
Spectral Graph Convolutional Networks With Lifting-based Adaptive Graph Wavelets
Spectral graph convolutional networks (SGCNs) have been attracting incre...
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07/04/2021
Bag of Instances Aggregation Boosts Self-supervised Learning
Recent advances in self-supervised learning have experienced remarkable ...
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06/18/2021
Message Passing in Graph Convolution Networks via Adaptive Filter Banks
Graph convolution networks, like message passing graph convolution netwo...
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06/08/2021
Multi-dataset Pretraining: A Unified Model for Semantic Segmentation
Collecting annotated data for semantic segmentation is time-consuming an...
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02/14/2021
Light Field Reconstruction via Attention-Guided Deep Fusion of Hybrid Lenses
This paper explores the problem of reconstructing high-resolution light ...
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12/07/2020
NCGNN: Node-level Capsule Graph Neural Network
Message passing has evolved as an effective tool for designing Graph Neu...
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12/04/2020
Hierarchical Semantic Aggregation for Contrastive Representation Learning
Self-supervised learning based on instance discrimination has shown rema...
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11/28/2020
Batch Normalization with Enhanced Linear Transformation
Batch normalization (BN) is a fundamental unit in modern deep networks, ...
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11/05/2020
Center-wise Local Image Mixture For Contrastive Representation Learning
Recent advances in unsupervised representation learning have experienced...
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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...
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09/10/2020
Key-Point Sequence Lossless Compression for Intelligent Video Analysis
Feature coding has been recently considered to facilitate intelligent vi...
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07/27/2020
K-Shot Contrastive Learning of Visual Features with Multiple Instance Augmentations
In this paper, we propose the K-Shot Contrastive Learning (KSCL) of visu...
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06/23/2020
Distilling Object Detectors with Task Adaptive Regularization
Current state-of-the-art object detectors are at the expense of high com...
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06/19/2020
Graph Pooling with Node Proximity for Hierarchical Representation Learning
Graph neural networks have attracted wide attentions to enable represent...
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05/09/2020
Human in Events: A Large-Scale Benchmark for Human-centric Video Analysis in Complex Events
Along with the development of the modern smart city, human-centric video...
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04/30/2020
TRP: Trained Rank Pruning for Efficient Deep Neural Networks
To enable DNNs on edge devices like mobile phones, low-rank approximatio...
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04/06/2020
Attribute Mix: Semantic Data Augmentation for Fine Grained Recognition
Collecting fine-grained labels usually requires expert-level domain know...
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01/17/2020
Latency-Aware Differentiable Neural Architecture Search
Differentiable neural architecture search methods became popular in auto...
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01/09/2020
Spatial-Temporal Transformer Networks for Traffic Flow Forecasting
Traffic forecasting has emerged as a core component of intelligent trans...
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12/29/2019
FLAT: Few-Shot Learning via Autoencoding Transformation Regularizers
One of the most significant challenges facing a few-shot learning task i...
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11/16/2019
AETv2: AutoEncoding Transformations for Self-Supervised Representation Learning by Minimizing Geodesic Distances in Lie Groups
Self-supervised learning by predicting transformations has demonstrated ...
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10/09/2019
Traned Rank Pruning for Efficient Deep Neural Networks
To accelerate DNNs inference, low-rank approximation has been widely ado...
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07/12/2019
PC-DARTS: Partial Channel Connections for Memory-Efficient Differentiable Architecture Search
Differentiable architecture search (DARTS) provided a fast solution in f...
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07/01/2019
iPool -- Information-based Pooling in Hierarchical Graph Neural Networks
With the advent of data science, the analysis of network or graph data h...
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06/20/2019
Probabilistic Tile Visibility-Based Server-Side Rate Adaptation for Adaptive 360-Degree Video Streaming
In this paper, we study the server-side rate adaptation problem for stre...
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05/17/2019
Group Re-Identification with Multi-grained Matching and Integration
The task of re-identifying groups of people underdifferent camera views ...
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05/06/2019
A multimodal lossless coding method for skeletons in videos
Nowadays, skeleton information in videos plays an important role in huma...
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05/05/2019
Optimization-based Decentralized Coded Caching for Files and Caches with Arbitrary Size
Existing decentralized coded caching solutions cannot guarantee small lo...
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02/02/2019
Multiuser Video Streaming Rate Adaptation: A Physical Layer Resource-Aware Deep Reinforcement Learning Approach
We consider a multi-user video streaming service optimization problem ov...
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12/06/2018
Trained Rank Pruning for Efficient Deep Neural Networks
The performance of Deep Neural Networks (DNNs) keeps elevating in recent...
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12/06/2018
DNQ: Dynamic Network Quantization
Network quantization is an effective method for the deployment of neural...
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04/25/2018