Search Results for author:
Found 32 papers, 3 papers with code
Patch-wise Auto-Encoder for Visual Anomaly Detection
Anomaly detection without priors of the anomalies is challenging.
Semi-supervised Object Detection: A Survey on Recent Research and Progress
In recent years, deep learning technology has been maturely applied in the field of object detection, and most algorithms tend to be supervised learning.
Application-Driven AI Paradigm for Person Counting in Various Scenarios
Person counting is considered as a fundamental task in video surveillance.
Application-Driven AI Paradigm for Hand-Held Action Detection
The first one is a coarse detection module with the human pose consisting of the whole hand, cigarette and head as target object.
Vision-Based Defect Classification and Weight Estimation of Rice Kernels
To compensate for the imbalance of different kernel numbers and classify kernels with multiple flaws accurately, we propose a multi-stage workflow which is able to locate the kernels in the captured image and classify their properties.
Application-Driven AI Paradigm for Human Action Recognition
Human action recognition in computer vision has been widely studied in recent years.
TAD: A Large-Scale Benchmark for Traffic Accidents Detection from Video Surveillance
After integration and annotation by various dimensions, a large-scale traffic accidents dataset named TAD is proposed in this work.
Data-Centric AI Paradigm Based on Application-Driven Fine-Grained Dataset Design
Deep learning has a wide range of applications in industrial scenario, but reducing false alarm (FA) remains a major difficulty.
Unsupervised Industrial Anomaly Detection via Pattern Generative and Contrastive Networks
After this, we use the Siamese-based network to compute the similarity of the generation image patch and original image patch.
A Waste Copper Granules Rating System Based on Machine Vision
Our rating network includes a segmentation network and a purity regression network, which respectively calculate the semantic segmentation heatmaps and purity results of the waste copper granules.
A Novel Speech-Driven Lip-Sync Model with CNN and LSTM
Generating synchronized and natural lip movement with speech is one of the most important tasks in creating realistic virtual characters.
A Survey on Unsupervised Anomaly Detection Algorithms for Industrial Images
In contrast, recent research shows that unsupervised learning has great potential in tackling the above disadvantages for visual industrial anomaly detection.
Appearance-Invariant 6-DoF Visual Localization using Generative Adversarial Networks
The visual localization network is composed of a feature extraction network and pose regression network.
How Old Are You? Face Age Translation with Identity Preservation Using GANs
We present a novel framework to generate images of different age while preserving identity information, which is known as face aging.
Small Obstacle Avoidance Based on RGB-D Semantic Segmentation
This paper presents a novel obstacle avoidance system for road robots equipped with RGB-D sensor that captures scenes of its way forward.
A Realistic Face-to-Face Conversation System based on Deep Neural Networks
Based on the models' output, the synthesizer uses the Pixel2Pixel model to generate realistic facial images.
A Neural Virtual Anchor Synthesizer based on Seq2Seq and GAN Models
This paper presents a novel framework to generate realistic face video of an anchor, who is reading certain news.
Video synthesis of human upper body with realistic face
This paper presents a generative adversarial learning-based human upper body video synthesis approach to generate an upper body video of target person that is consistent with the body motion, face expression, and pose of the person in source video.
Deep Learning based Wearable Assistive System for Visually Impaired People
In this paper, we propose a deep learning based assistive system to improve the environment perception experience of visually impaired (VI).
Falls Prediction Based on Body Keypoints and Seq2Seq Architecture
This paper presents a novel approach for predicting the falls of people in advance from monocular video.
DeepVIO: Self-supervised Deep Learning of Monocular Visual Inertial Odometry using 3D Geometric Constraints
This paper presents an self-supervised deep learning network for monocular visual inertial odometry (named DeepVIO).
Vision-based Robotic Grasping From Object Localization, Object Pose Estimation to Grasp Estimation for Parallel Grippers: A Review
We conclude three key tasks during vision-based robotic grasping, which are object localization, object pose estimation and grasp estimation.
Feature Aggregation Network for Video Face Recognition
We make the following contributions: first, we propose a meta attention-based aggregation scheme which adaptively and fine-grained weighs the feature along each feature dimension among all frames to form a compact and discriminative representation.
Towards More Realistic Human-Robot Conversation: A Seq2Seq-based Body Gesture Interaction System
This paper presents a novel system that enables intelligent robots to exhibit realistic body gestures while communicating with humans.
Virtual-Blind-Road Following Based Wearable Navigation Device for Blind People
To help the blind people walk to the destination efficiently and safely in indoor environment, a novel wearable navigation device is presented in this paper.
Deep Learning Based Robot for Automatically Picking up Garbage on the Grass
In addition, with the ground segmentation using a deep neural network, a novel navigation strategy is proposed to guide the robot to move around.
Facial Pose Estimation by Deep Learning from Label Distributions
Facial pose estimation has gained a lot of attentions in many practical applications, such as human-robot interaction, gaze estimation and driver monitoring.
Synthetic Data Generation and Adaption for Object Detection in Smart Vending Machines
This paper presents an improved scheme for the generation and adaption of synthetic images for the training of deep Convolutional Neural Networks(CNNs) to perform the object detection task in smart vending machines.
A Survey on Face Data Augmentation
The quality and size of training set have great impact on the results of deep learning-based face related tasks.
A Unified Framework for Mutual Improvement of SLAM and Semantic Segmentation
This paper presents a novel framework for simultaneously implementing localization and segmentation, which are two of the most important vision-based tasks for robotics.
Deep Global-Relative Networks for End-to-End 6-DoF Visual Localization and Odometry
Although a wide variety of deep neural networks for robust Visual Odometry (VO) can be found in the literature, they are still unable to solve the drift problem in long-term robot navigation.
