research
∙
07/26/2023
Adaptive Frequency Filters As Efficient Global Token Mixers
Recent vision transformers, large-kernel CNNs and MLPs have attained rem...
share
research
∙
06/02/2023
Responsible Task Automation: Empowering Large Language Models as Responsible Task Automators
The recent success of Large Language Models (LLMs) signifies an impressi...
research
∙
04/25/2023
Learning Trajectories are Generalization Indicators
The aim of this paper is to investigate the connection between learning ...
research
∙
04/11/2023
MRVM-NeRF: Mask-Based Pretraining for Neural Radiance Fields
Most Neural Radiance Fields (NeRFs) have poor generalization ability, li...
research
∙
03/09/2023
Unifying Layout Generation with a Decoupled Diffusion Model
Layout generation aims to synthesize realistic graphic scenes consisting...
research
∙
01/21/2023
Versatile Neural Processes for Learning Implicit Neural Representations
Representing a signal as a continuous function parameterized by neural n...
research
∙
07/05/2022
Image Coding for Machines with Omnipotent Feature Learning
Image Coding for Machines (ICM) aims to compress images for AI tasks ana...
research
∙
03/23/2022
Deep Frequency Filtering for Domain Generalization
Improving the generalization capability of Deep Neural Networks (DNNs) i...
research
∙
03/11/2022
ActiveMLP: An MLP-like Architecture with Active Token Mixer
This paper presents ActiveMLP, a general MLP-like backbone for computer ...
research
∙
01/28/2022
Mask-based Latent Reconstruction for Reinforcement Learning
For deep reinforcement learning (RL) from pixels, learning effective sta...
research
∙
12/26/2021
Learning Cross-Scale Prediction for Efficient Neural Video Compression
In this paper, we present the first neural video codec that can compete ...
research
∙
12/13/2021
Lifelong Unsupervised Domain Adaptive Person Re-identification with Coordinated Anti-forgetting and Adaptation
Unsupervised domain adaptive person re-identification (ReID) has been ex...
research
∙
12/06/2021
SelectAugment: Hierarchical Deterministic Sample Selection for Data Augmentation
Data augmentation (DA) has been widely investigated to facilitate model ...
research
∙
11/30/2021
MMPTRACK: Large-scale Densely Annotated Multi-camera Multiple People Tracking Benchmark
Multi-camera tracking systems are gaining popularity in applications tha...
research
∙
11/26/2021
Confounder Identification-free Causal Visual Feature Learning
Confounders in deep learning are in general detrimental to model's gener...
research
∙
11/05/2021
Versatile Learned Video Compression
Learned video compression methods have demonstrated great promise in cat...
research
∙
07/31/2021
Pose-Guided Feature Learning with Knowledge Distillation for Occluded Person Re-Identification
Occluded person re-identification (ReID) aims to match person images wit...
research
∙
06/30/2021
Dual Aspect Self-Attention based on Transformer for Remaining Useful Life Prediction
Remaining useful life prediction (RUL) is one of the key technologies of...
research
∙
03/25/2021
Disentanglement-based Cross-Domain Feature Augmentation for Effective Unsupervised Domain Adaptive Person Re-identification
Unsupervised domain adaptive (UDA) person re-identification (ReID) aims ...
research
∙
12/17/2020
Learned Block-based Hybrid Image Compression
Learned image compression based on neural networks have made huge progre...
research
∙
12/16/2020
Exploiting Sample Uncertainty for Domain Adaptive Person Re-Identification
Many unsupervised domain adaptive (UDA) person re-identification (ReID) ...
research
∙
12/11/2020
Learning Omni-frequency Region-adaptive Representations for Real Image Super-Resolution
Traditional single image super-resolution (SISR) methods that focus on s...
research
∙
11/19/2020
Latent-Separated Global Prediction for Learned Image Compression
Over the past several years, we have witnessed the impressive progress o...
research
∙
11/09/2020
A Syntactic Approach to Studying Strongly Equivalent Logic Programs
In the field of Answer Set Programming (ASP), two logic programs are str...
research
∙
10/09/2020
Uncertainty-Aware Few-Shot Image Classification
Few-shot image classification aims to learn to recognize new categories ...
research
∙
06/08/2020
Rethinking Classification Loss Designs for Person Re-identification with a Unified View
Person Re-identification (ReID) aims at matching a person of interest ac...
research
∙
05/16/2020
Multi-scale Grouped Dense Network for VVC Intra Coding
Versatile Video Coding (H.266/VVC) standard achieves better image qualit...
research
∙
03/27/2020
Multi-Granularity Reference-Aided Attentive Feature Aggregation for Video-based Person Re-identification
Video-based person re-identification (reID) aims at matching the same pe...
research
∙
11/23/2019
Region Normalization for Image Inpainting
Feature Normalization (FN) is an important technique to help neural netw...
research
∙
09/18/2019
On the Strong Equivalences of LPMLN Programs
By incorporating the methods of Answer Set Programming (ASP) and Markov ...
research
∙
09/09/2019
On the Strong Equivalences for LPMLN Programs
LPMLN is a powerful knowledge representation and reasoning tool that com...
research
∙
06/08/2019
A Coarse-to-Fine Framework for Learned Color Enhancement with Non-Local Attention
Automatic color enhancement are aimed to automaticly and adaptively adju...
research
∙
04/17/2019
CaseNet: Content-Adaptive Scale Interaction Networks for Scene Parsing
Objects in an image exhibit diverse scales. Adaptive receptive fields ar...
research
∙
04/05/2019
Relation-Aware Global Attention
Attention mechanism aims to increase the representation power by focusin...
research
∙
03/03/2019
Asynchronous Episodic Deep Deterministic Policy Gradient: Towards Continuous Control in Computationally Complex Environments
Deep Deterministic Policy Gradient (DDPG) has been proved to be a succes...
research
∙
12/22/2018
Learned Scalable Image Compression with Bidirectional Context Disentanglement Network
In this paper, we propose a learned scalable/progressive image compressi...
research
∙
12/21/2018
Densely Semantically Aligned Person Re-Identification
We propose a densely semantically aligned person re-identification (re-I...
research
∙
04/02/2018
Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments
In the NIPS 2017 Learning to Run challenge, participants were tasked wit...
research
∙
05/14/2014