research
∙
09/18/2023
VisualProg Distiller: Learning to Fine-tune Non-differentiable Visual Programming Frameworks
As an interpretable and universal neuro-symbolic paradigm based on Large...
share
research
∙
11/08/2021
Enhancing Prototypical Few-Shot Learning by Leveraging the Local-Level Strategy
Aiming at recognizing the samples from novel categories with few referen...
research
∙
09/03/2021
CX-ToM: Counterfactual Explanations with Theory-of-Mind for Enhancing Human Trust in Image Recognition Models
We propose CX-ToM, short for counterfactual explanations with theory-of ...
research
∙
04/18/2021
Solving Inefficiency of Self-supervised Representation Learning
Self-supervised learning has attracted great interest due to its tremend...
research
∙
11/30/2020
Continuous Transition: Improving Sample Efficiency for Continuous Control Problems via MixUp
Although deep reinforcement learning (RL) has been successfully applied ...
research
∙
03/23/2020
Linguistically Driven Graph Capsule Network for Visual Question Reasoning
Recently, studies of visual question answering have explored various arc...
research
∙
03/14/2020
Learning Reinforced Agents with Counterfactual Simulation for Medical Automatic Diagnosis
Medical automatic diagnosis (MAD) aims to learn an agent that mimics the...
research
∙
05/29/2019
Instance-Aware Representation Learning and Association for Online Multi-Person Tracking
Multi-Person Tracking (MPT) is often addressed within the detection-to-a...
research
∙
05/04/2019
Face Hallucination by Attentive Sequence Optimization with Reinforcement Learning
Face hallucination is a domain-specific super-resolution problem that ai...
research
∙
04/07/2019
Adaptively Connected Neural Networks
This paper presents a novel adaptively connected neural network (ACNet) ...
research
∙
01/12/2019
3D Human Pose Machines with Self-supervised Learning
Driven by recent computer vision and robotic applications, recovering 3D...
research
∙
06/30/2018
Cost-effective Object Detection: Active Sample Mining with Switchable Selection Criteria
Though quite challenging, the training of object detectors using large-s...
research
∙
03/27/2018
Towards Human-Machine Cooperation: Self-supervised Sample Mining for Object Detection
Though quite challenging, leveraging large-scale unlabeled or partially ...
research
∙
07/31/2017
Recurrent 3D Pose Sequence Machines
3D human articulated pose recovery from monocular image sequences is ver...
research
∙
07/28/2017
Deep Co-Space: Sample Mining Across Feature Transformation for Semi-Supervised Learning
Aiming at improving performance of visual classification in a cost-effec...
research
∙
07/26/2017
Structure-Preserving Image Super-resolution via Contextualized Multi-task Learning
Single image super resolution (SR), which refers to reconstruct a higher...
research
∙
01/13/2017
Active Self-Paced Learning for Cost-Effective and Progressive Face Identification
This paper aims to develop a novel cost-effective framework for face ide...
research
∙
01/13/2017
Cost-Effective Active Learning for Deep Image Classification
Recent successes in learning-based image classification, however, heavil...
research
∙
08/13/2016
Human Pose Estimation from Depth Images via Inference Embedded Multi-task Learning
Human pose estimation (i.e., locating the body parts / joints of a perso...
research
∙
07/25/2016
Local- and Holistic- Structure Preserving Image Super Resolution via Deep Joint Component Learning
Recently, machine learning based single image super resolution (SR) appr...
research
∙
12/05/2015
A Deep Structured Model with Radius-Margin Bound for 3D Human Activity Recognition
Understanding human activity is very challenging even with the recently ...
research
∙
01/26/2015