Ching-Chun Huang

• Professor (Associate) at National Yang Ming Chiao Tung University

Recently, diffusion-based blind super-resolution (SR) methods have shown great ability to generate high-resolution images with abundant high-frequency detail, but the detail is often achieved at the expense of fidelity. Meanwhile, another line of research focusing on rectifying the reverse process of diffusion models (i.e., diffusion guidance), has...

This study primarily focused on developing a system to generate simulated computed tomography pulmonary angiography (CTPA) images for pulmonary embolism diagnosis and aiding medical practitioners gain a more intuitive understanding of the occurrence of pulmonary embolism (PE) in diagnosis. Compared to existing methods, this system provides a non-in...

Rescaling digital images for display on various devices, while simultaneously removing noise, has increasingly become a focus of attention. However, limited research has been done on a unified framework that can efficiently perform both tasks. In response, we propose INDIRECT (INvertible and Discrete noisy Image Rescaling with Enhancement from Case...

In heavy rain situations, the clarity of both human vision and computer vision is significantly reduced. Rain removal GAN-based networks have been proposed as a means of resolving this problem. However, such methods have only a limited effectiveness in improving the object detection accuracy. Accordingly, this study commences by analyzing the objec...

The SOTA methods proposed voxelization or pillarization to regularize unordered point clouds, improving computing efficiency for LiDAR-based 3D object detection. However, they usually trade partial accuracy for speed. Thus, we bring up a new problem setting: “Is it possible to keep high detection accuracy while point-cloud quantization is applied?”...

Advanced object detection techniques have been widely studied in recent years and have been successfully applied in real-world applications. However, existing algorithms may struggle with nighttime image detection, especially in low-luminance conditions. Researchers have attempted to overcome this issue by collecting large amounts of multi-domain d...

This study established a feature-enhanced adversarial semi-supervised semantic segmentation model to automatically annotate pulmonary embolism (PE) lesion areas in computed tomography pulmonary angiogram (CTPA) images. In the current study, all of the PE CTPA image segmentation methods were trained by supervised learning. However, when CTPA images...

Rescaling digital photos to display them on heterogeneous devices while removing the noise has gradually gained attention. However, little research focused on a unified framework to perform these tasks jointly and efficiently. We propose a novel method, INDIRECT (INvertible and Discrete noisy Image Rescaling with Enhancement from Case-dependent Tex...

This paper aims to estimate indoor occupancy given the real-time observed signals from the existing sensors; next, as a practical application, we build a dynamic control schedule for energy saving based on the estimated indoor occupancy. However, several issues need to be addressed. First, it is impossible to train the model with rich labels due to...

This paper proposes a novel task-consistency learning method that enables us to train a vacant space detection network (target task) based on the logic consistency with the semantic outcomes from a flow-based motion behavior classifier (source task) in a parking lot. Note that the source task can introduce false detection during task-consistency le...

Photo exposure correction is widely investigated, but fewer studies focus on correcting under and over-exposed images simultaneously. Three issues remain open to handle and correct under and over-exposed images in a unified way. First, a locally-adaptive exposure adjustment may be more flexible instead of learning a global mapping. Second, it is an...

Photo by Olena Sergienko on Unsplash What is it about? Cross-resolution face recognition (CRFR) in an open-set setting is a practical application for surveillance scenarios where low-resolution (LR) probe faces captured via surveillance cameras require being matched to a watchlist of high-resolution (HR) galleries. Although CRFR is to be of practic...

This study established a feature-enhanced adversarial semi-supervised semantic segmentation model to automatically annotate pulmonary embolism lesion areas in computed tomography pulmonary angiogram (CTPA) images. In current studies, all of the PE CTPA image segmentation methods are trained by supervised learning. However, the supervised learning m...

In this paper, we proposed a multi-view system for 3D human skeleton tracking based on multi-cue fusion. Multiple Kinect version 2 cameras are applied to build up a low-cost system. Though Kinect cameras can detect 3D skeleton from their depth sensors, some challenges of skeleton extraction still exist, such as left–right confusion and severe self-...

3D point-cloud upsampling, a crucial perceptual module to help us understand the complex scene and object, aims to generate a high-resolution point cloud given a sparse point set. While considerable attention has been paid to single object point-cloud upsampling, literature on upsampling complex scenes has emerged slowly. Remarkably, few related wo...

Most of the existing algorithms for zero-shot classification problems typically rely on the attribute-based semantic relations among categories to realize the classification of novel categories without observing any of their instances. However, training the zero-shot classification models still requires attribute labeling for each class (or even in...

Background Rapid on-site cytologic evaluation (ROSE) helps to improve the diagnostic accuracy in endobronchial ultrasound (EBUS) procedures. However, cytologists are seldom available to perform ROSE in many institutions. Recent studies have investigated the application of deep learning in cytologic image analysis. As such, the present study analyze...

Complementary metal-oxide-semiconductor (CMOS) image sensors can cause noise in images collected or transmitted in unfavorable environments, especially low-illumination scenarios. Numerous approaches have been developed to solve the problem of image noise removal. However, producing natural and high-quality denoised images remains a crucial challen...

This paper addresses the video rescaling task, which arises from the needs of adapting the video spatial resolution to suit individual viewing devices. We aim to jointly optimize video downscaling and upscaling as a combined task. Most recent studies focus on image-based solutions, which do not consider temporal information. We present two joint op...

Vision perception is one of the most important components for a computer or robot to understand the surrounding scene and achieve autonomous applications. However, most of the vision models are based on the RGB sensors, which in general are vulnerable to the insufficient lighting condition. In contrast, the depth camera, another widely-used visual...

Self-driving cars usually leverage on semantic segmentation to perceive objects in an urban scene. However, it is costly to annotate a large dataset to train a network for semantic segmentation. Which is why synthetic datasets are commonly used as a substitute for training semantic segmentation models. Unfortunately, networks trained on synthetic d...

To avoid distributed denial-of-service (DDoS) attacks or real-time transmission control protocol (TCP) incast in the software-defined networking (SDN) environment, the HashPipe algorithm was developed following the space-saving approach. Unfortunately, HashPipe implemented in the behavioral model (bmv2) cannot be directly executed at a real program...

In this paper, we propose novel approaches that utilize the header manipulations of the P4 (Programming Protocol-Independent Packet Processor) switches to aggregate small IoT packets into a large one, transmit it over a network, and then disaggregate it back to the original small packets, all in the data plane of the hardware P4 switch to provide h...

Inspecting X-ray images is an essential aspect of medical diagnosis. However, due to an X-ray's low contrast and low dynamic range, important aspects such as organs, bones, and nodules become difficult to identify. Hence, contrast adjustment is critical, especially in view of its ability to enhance the details in both bright and dark regions. For X...

In many Internet of Things (IoT) applications, large numbers of small sensor data are delivered in the network, which may cause heavy traffics. To reduce the number of messages delivered from the sensor devices to the IoT server, a promising approach is to aggregate several small IoT messages into a large packet before they are delivered through th...

Nowadays, deep learning methods, especially CNNs, have achieved many promising results in a wide range of computer vision applications. However, few studies focused on designing suitable deep learning methods for parking space status inference. As we have known, it is challenging to detect parking spaces in an outdoor environment due to dynamic lig...

This work proposes a personalized mobile learning system using smart glasses which include outward and inward facing cameras. By using the outward facing camera, the proposed system recognizes the QR code, and then discovers the front view of a wearer. Additionally, our system employs an inward facing camera to capture eye images, find out the cent...

In order to solve the unsupervised domain adaptation problem, some methods based on adversarial learning are proposed recently. These methods greatly attract people's eyes because of the better ability to learn the common representation space so that the feature distributions among many domains are ambiguous and non-discriminative. Although there a...

Endoscopic surgery causes less tissue injury compared to open surgical techniques, thus promoting more rapid recuperation and reduced post-operative pain. Endoscopy, however, allows the surgeon to visualise only the anatomical surface of the surgical site, with a relatively narrow field of view. Moreover, the 2D video captured by the conventional e...

By fusing a sequence of exposure images, we could generate a high dynamic range (HDR) image and enhance the image details. However, to display the HDR image on a low dynamic range (LDR) device, HDR compression is necessary. In the paper, a new method for HDR Compression based on matting Laplacian is proposed. The major assumption behind is that the...

In a practical environment, the viewing angle and height of a video surveillance camera are uncontrollable. This may cause severe inter-object occlusion and complicate the detection problem. In this paper, we proposed a novel inference framework with multiple layers forvacantparking space detection. The framework consists of an Image layer, a Patch...

During the past decades, many fingerprint-based indoor positioning systems have been proposed and have achieved great success. However, uncontrolled effects of device diversity, signal noise, and dynamic obstacles could recognizably degrade the performance of modern fingerprint-based indoor localization systems. In this paper, to amend the variatio...

Introduction: Endoscopic surgery causes reduced injury to tissues which helps in rapid recovery and less painful post-operative period of patients. However, its narrow field of view and loss of depth perception in endoscope image make surgeon's task difficult. Moreover, in endoscopic surgery surgeons can only see the surface of the surgical anatomy...

In this paper, we proposed a new multi-layer discriminative framework for vacant parking space detection. From bottom to top, the framework consists of an image feature extraction layer, a patch classification layer, a weighted combination layer, and a status inference layer. In the feature extraction layer, the framework extracts lighting-invarian...

Recently, Huang's method [1] has proposed to use a 3D parking space representation for parking space detection. Following a generative process, the approach treats a parking lot as the collection of many parking spaces. Each space is modeled by a 3D cube. Each 3D cube is composed of multiple 3D surfaces. If projecting those 3D surfaces onto the ima...

A method for automatically detecting and tracking multiple targets in a multi-camera surveillance zone and system thereof. In each camera view of the system only a simple object detection algorithm is needed. The detection results from multiple cameras are fused into a posterior distribution, named TDP, based on the Bayesian rule. This TDP distribu...

Introduction: Endoscopy is widely used in the surgical world. Reduced surgical injury during endoscopic surgery makes the patient’s life easy. However, the endoscopic surgery becomes a challenge for the novice surgeons because of the narrow field of view and the lack of 3D perception in the 2D endoscope image. Such limitations of the endoscope may...

In this paper, we proposed a crowd-sensing idea to construct the driving environment so that the driver could have better understanding of his/her surroundings on the roadway. We assume that intelligent vehicles will embed a sensing system, which is composed of three basic modules including inter-vehicle communication, vehicle license plate verific...

In this paper, we proposed a crowd-sensing idea to construct the driving environment so that the driver could have better understanding of his/her surroundings on the roadway. We assume that intelligent vehicles will embed a sensing system, which is composed of three basic modules including inter-vehicle communication, vehicle license plate verific...

X-ray imaging is an efficient tool for health inspection. The energy of received X-ray could reveal the density inside human body and be represented in an X-ray image. In general, the bright regions of an X-ray image are of interest since most important matters compactly locating in those regions. However, the low contrast property of the bright re...

Pulmonary edema, i.e. excess of extravascular fluid in lungs, is a common manifestation of various clinical conditions. Although the etiology of the pulmonary edema is deduced with the help of history, physical examination and various biochemical and radiological investigations, computer aided evaluation of pulmonary edema will be helpful for physi...

Using camera networks to monitor the trajectory of moving vehicles plays important role in many applications, such as video surveillance, intelligent traffic system, and social security management. Most of the previous works tried to track the moving vehicle by using either appearance matching or spatial and temporal information. However, we realiz...

3D instrument reconstruction and tracking are critical steps in minimally invasive surgery. Nowadays, some image-based methods have been proposed. Trying to minimize the damage to human body, those systems only used one camera as the major sensor to track and reconstruct the instrument and hence lost performance. For performance improvement, an ine...