434 citations · 1.6k across the 63 of their papers we have counts for
64 papers
CAPQ-FAST: Content-Adaptive Perceived Quality Assessment for Faster Audiovisual Playback
Jiarun Song, Yuxin Song, Fuzheng Yang +1
Faster playback has become a common feature in modern online audiovisual services, allowing users to consume content in less time while still maintaining a coherent viewing experie…
IPDiff: Diffusion-driven ORSI Salient Object Detection with Information Reconstruction and Multi-Prior Guidance
Gongyang Li, Zhen Bai, Runmin Cong +3
Existing Salient Object Detection in Optical Remote Sensing Image (ORSI-SOD) methods mainly adopt the static inference strategy, which uses fixed trained model parameters for salie…
Context-Aware Deep Learning for Multi Modal Depression Detection
Genevieve Lam, Huang Dongyan, Weisi Lin
In this study, we focus on automated approaches to detect depression from clinical interviews using multi-modal machine learning (ML). Our approach differentiates from other succes…
Efficient Joint Optimization of Layer-Adaptive Weight Pruning in Deep Neural Networks
Kaixin Xu, Zhe Wang, Xue Geng +4
In this paper, we propose a novel layer-adaptive weight-pruning approach for Deep Neural Networks (DNNs) that addresses the challenge of optimizing the output distortion minimizati…
Local Distortion Aware Efficient Transformer Adaptation for Image Quality Assessment
Kangmin Xu, Liang Liao, Jing Xiao +4
Image Quality Assessment (IQA) constitutes a fundamental task within the field of computer vision, yet it remains an unresolved challenge, owing to the intricate distortion conditi…
TOPIQ: A Top-down Approach from Semantics to Distortions for Image Quality Assessment
Chaofeng Chen, Jiadi Mo, Jingwen Hou +5
Image Quality Assessment (IQA) is a fundamental task in computer vision that has witnessed remarkable progress with deep neural networks. Inspired by the characteristics of the hum…
Advancing Zero-Shot Digital Human Quality Assessment through Text-Prompted Evaluation
Zicheng Zhang, Wei Sun, Yingjie Zhou +6
Digital humans have witnessed extensive applications in various domains, necessitating related quality assessment studies. However, there is a lack of comprehensive digital human q…
Regression-free Blind Image Quality Assessment with Content-Distortion Consistency
Xiaoqi Wang, Jian Xiong, Hao Gao +1
The optimization objective of regression-based blind image quality assessment (IQA) models is to minimize the mean prediction error across the training dataset, which can lead to b…
You Can Mask More For Extremely Low-Bitrate Image Compression
Anqi Li, Feng Li, Jiaxin Han +6
Learned image compression (LIC) methods have experienced significant progress during recent years. However, these methods are primarily dedicated to optimizing the rate-distortion…
AGIQA-3K: An Open Database for AI-Generated Image Quality Assessment
Chunyi Li, Zicheng Zhang, Haoning Wu +5
With the rapid advancements of the text-to-image generative model, AI-generated images (AGIs) have been widely applied to entertainment, education, social media, etc. However, cons…
GMS-3DQA: Projection-based Grid Mini-patch Sampling for 3D Model Quality Assessment
Zicheng Zhang, Wei Sun, Houning Wu +5
Nowadays, most 3D model quality assessment (3DQA) methods have been aimed at improving performance. However, little attention has been paid to the computational cost and inference…
Towards Explainable In-the-Wild Video Quality Assessment: A Database and a Language-Prompted Approach
Haoning Wu, Erli Zhang, Liang Liao +6
The proliferation of in-the-wild videos has greatly expanded the Video Quality Assessment (VQA) problem. Unlike early definitions that usually focus on limited distortion types, VQ…
Towards Robust Text-Prompted Semantic Criterion for In-the-Wild Video Quality Assessment
Haoning Wu, Liang Liao, Annan Wang +5
The proliferation of videos collected during in-the-wild natural settings has pushed the development of effective Video Quality Assessment (VQA) methodologies. Contemporary supervi…
The First Comprehensive Dataset with Multiple Distortion Types for Visual Just-Noticeable Differences
Yaxuan Liu, Jian Jin, Yuan Xue +1
Recently, with the development of deep learning, a number of Just Noticeable Difference (JND) datasets have been built for JND modeling. However, all the existing JND datasets only…
JND-Based Perceptual Optimization For Learned Image Compression
Feng Ding, Jian Jin, Lili Meng +1
Recently, learned image compression schemes have achieved remarkable improvements in image fidelity (e.g., PSNR and MS-SSIM) compared to conventional hybrid image coding ones due t…
Blind Multimodal Quality Assessment of Low-light Images
Miaohui Wang, Zhuowei Xu, Mai Xu +1
Blind image quality assessment (BIQA) aims at automatically and accurately forecasting objective scores for visual signals, which has been widely used to monitor product and servic…
MetaGrad: Adaptive Gradient Quantization with Hypernetworks
Kaixin Xu, Alina Hui Xiu Lee, Ziyuan Zhao +3
A popular track of network compression approach is Quantization aware Training (QAT), which accelerates the forward pass during the neural network training and inference. However,…
Exploring Opinion-unaware Video Quality Assessment with Semantic Affinity Criterion
Haoning Wu, Liang Liao, Jingwen Hou +6
Recent learning-based video quality assessment (VQA) algorithms are expensive to implement due to the cost of data collection of human quality opinions, and are less robust across…
Evaluating the Efficacy of Skincare Product: A Realistic Short-Term Facial Pore Simulation
Ling Li, Bandara Dissanayake, Tatsuya Omotezako +8
Simulating the effects of skincare products on face is a potential new way to communicate the efficacy of skincare products in skin diagnostics and product recommendations. Further…
Lightweight Salient Object Detection in Optical Remote-Sensing Images via Semantic Matching and Edge Alignment
Gongyang Li, Zhi Liu, Xinpeng Zhang +1
Recently, relying on convolutional neural networks (CNNs), many methods for salient object detection in optical remote sensing images (ORSI-SOD) are proposed. However, most methods…
Bridging Component Learning with Degradation Modelling for Blind Image Super-Resolution
Yixuan Wu, Feng Li, Huihui Bai +3
Convolutional Neural Network (CNN)-based image super-resolution (SR) has exhibited impressive success on known degraded low-resolution (LR) images. However, this type of approach i…
Learning Detail-Structure Alternative Optimization for Blind Super-Resolution
Feng Li, Yixuan Wu, Huihui Bai +3
Existing convolutional neural networks (CNN) based image super-resolution (SR) methods have achieved impressive performance on bicubic kernel, which is not valid to handle unknown…
KSS-ICP: Point Cloud Registration based on Kendall Shape Space
Chenlei Lv, Weisi Lin, Baoquan Zhao
Point cloud registration is a popular topic which has been widely used in 3D model reconstruction, location, and retrieval. In this paper, we propose a new registration method, KSS…
IntegratedPIFu: Integrated Pixel Aligned Implicit Function for Single-view Human Reconstruction
Kennard Yanting Chan, Guosheng Lin, Haiyu Zhao +1
We propose IntegratedPIFu, a new pixel aligned implicit model that builds on the foundation set by PIFuHD. IntegratedPIFu shows how depth and human parsing information can be predi…