Search Results for author: Shiqi Wang

Found 141 papers, 67 papers with code

LL-ICM: Image Compression for Low-level Machine Vision via Large Vision-Language Model

no code implementations5 Dec 2024 Yuan Xue, Qi Zhang, Chuanmin Jia, Shiqi Wang

By jointly optimizing compression and LL tasks, the proposed LL-ICM not only enriches its encoding ability in generalizing to versatile LL tasks but also optimizes the processing ability of down-stream LL task models, achieving mutual adaptation for image codecs and LL task models.

Image Compression Image Restoration +4

An Information-Theoretic Regularizer for Lossy Neural Image Compression

no code implementations23 Nov 2024 Yingwen Zhang, Meng Wang, Xihua Sheng, Peilin Chen, Junru Li, Li Zhang, Shiqi Wang

Lossy image compression networks aim to minimize the latent entropy of images while adhering to specific distortion constraints.

Image Compression

Compact Visual Data Representation for Green Multimedia -- A Human Visual System Perspective

no code implementations21 Nov 2024 Peilin Chen, Xiaohan Fang, Meng Wang, Shiqi Wang, Siwei Ma

The Human Visual System (HVS), with its intricate sophistication, is capable of achieving ultra-compact information compression for visual signals.

Mitigating Perception Bias: A Training-Free Approach to Enhance LMM for Image Quality Assessment

no code implementations19 Nov 2024 Siyi Pan, Baoliang Chen, Danni Huang, Hanwei Zhu, Lingyu Zhu, Xiangjie Sui, Shiqi Wang

By applying these specific distortions to the query or test images, we ensure that the degraded images are recognized as poor quality while their semantics remain.

Image Captioning Image Quality Assessment

Large Language Models for Lossless Image Compression: Next-Pixel Prediction in Language Space is All You Need

no code implementations19 Nov 2024 Kecheng Chen, Pingping Zhang, Hui Liu, Jie Liu, Yibing Liu, Jiaxin Huang, Shiqi Wang, Hong Yan, Haoliang Li

We have recently witnessed that ``Intelligence" and `` Compression" are the two sides of the same coin, where the language large model (LLM) with unprecedented intelligence is a general-purpose lossless compressor for various data modalities.

Attribute Image Compression

Standardizing Generative Face Video Compression using Supplemental Enhancement Information

no code implementations19 Oct 2024 Bolin Chen, Yan Ye, Jie Chen, Ru-Ling Liao, Shanzhi Yin, Shiqi Wang, Kaifa Yang, Yue Li, Yiling Xu, Ye-kui Wang, Shiv Gehlot, Guan-Ming Su, Peng Yin, Sean McCarthy, Gary J. Sullivan

This paper proposes a Generative Face Video Compression (GFVC) approach using Supplemental Enhancement Information (SEI), where a series of compact spatial and temporal representations of a face video signal (i. e., 2D/3D key-points, facial semantics and compact features) can be coded using SEI message and inserted into the coded video bitstream.

Video Compression

Test-time adaptation for image compression with distribution regularization

no code implementations16 Oct 2024 Kecheng Chen, Pingping Zhang, Tiexin Qin, Shiqi Wang, Hong Yan, Haoliang Li

Current test- or compression-time adaptation image compression (TTA-IC) approaches, which leverage both latent and decoder refinements as a two-step adaptation scheme, have potentially enhanced the rate-distortion (R-D) performance of learned image compression models on cross-domain compression tasks, \textit{e. g.,} from natural to screen content images.

Decoder Image Compression +1

Generative Human Video Compression with Multi-granularity Temporal Trajectory Factorization

no code implementations14 Oct 2024 Shanzhi Yin, Bolin Chen, Shiqi Wang, Yan Ye

In this paper, we propose a novel Multi-granularity Temporal Trajectory Factorization framework for generative human video compression, which holds great potential for bandwidth-constrained human-centric video communication.

Video Compression

Compressing Scene Dynamics: A Generative Approach

1 code implementation13 Oct 2024 Shanzhi Yin, Zihan Zhang, Bolin Chen, Shiqi Wang, Yan Ye

This paper proposes to learn generative priors from the motion patterns instead of video contents for generative video compression.

Decoder Video Compression

Beyond GFVC: A Progressive Face Video Compression Framework with Adaptive Visual Tokens

1 code implementation11 Oct 2024 Bolin Chen, Shanzhi Yin, Zihan Zhang, Jie Chen, Ru-Ling Liao, Lingyu Zhu, Shiqi Wang, Yan Ye

Recently, deep generative models have greatly advanced the progress of face video coding towards promising rate-distortion performance and diverse application functionalities.

Motion Estimation Philosophy +1

Multimodal Clickbait Detection by De-confounding Biases Using Causal Representation Inference

no code implementations10 Oct 2024 Jianxing Yu, Shiqi Wang, Han Yin, Zhenlong Sun, Ruobing Xie, Bo Zhang, Yanghui Rao

Considering these features are often mixed up with unknown biases, we then disentangle three kinds of latent factors from them, including the invariant factor that indicates intrinsic bait intention; the causal factor which reflects deceptive patterns in a certain scenario, and non-causal noise.

Causal Inference Clickbait Detection

Towards Next-Generation LLM-based Recommender Systems: A Survey and Beyond

1 code implementation10 Oct 2024 Qi Wang, Jindong Li, Shiqi Wang, Qianli Xing, Runliang Niu, He Kong, Rui Li, Guodong Long, Yi Chang, Chengqi Zhang

Large language models (LLMs) have not only revolutionized the field of natural language processing (NLP) but also have the potential to bring a paradigm shift in many other fields due to their remarkable abilities of language understanding, as well as impressive generalization capabilities and reasoning skills.

Large Language Model Recommendation Systems

RCNet: Deep Recurrent Collaborative Network for Multi-View Low-Light Image Enhancement

1 code implementation6 Sep 2024 Hao Luo, Baoliang Chen, Lingyu Zhu, Peilin Chen, Shiqi Wang

Recent single image-based enhancement methods may not be able to provide consistently desirable restoration performance for all views due to the ignorance of potential feature correspondence among different views.

Low-Light Image Enhancement Scene Understanding +1

Image Provenance Analysis via Graph Encoding with Vision Transformer

no code implementations26 Aug 2024 Keyang Zhang, Chenqi Kong, Shiqi Wang, Anderson Rocha, Haoliang Li

Recent advances in AI-powered image editing tools have significantly lowered the barrier to image modification, raising pressing security concerns those related to spreading misinformation and disinformation on social platforms.

graph construction Misinformation

Unrolled Decomposed Unpaired Learning for Controllable Low-Light Video Enhancement

1 code implementation22 Aug 2024 Lingyu Zhu, Wenhan Yang, Baoliang Chen, Hanwei Zhu, Zhangkai Ni, Qi Mao, Shiqi Wang

To address the above challenge, we propose the Unrolled Decomposed Unpaired Network (UDU-Net) for enhancing low-light videos by unrolling the optimization functions into a deep network to decompose the signal into spatial and temporal-related factors, which are updated iteratively.

Low-Light Image Enhancement Video Enhancement

Reward Difference Optimization For Sample Reweighting In Offline RLHF

no code implementations18 Aug 2024 Shiqi Wang, Zhengze Zhang, Rui Zhao, Fei Tan, Cam Tu Nguyen

Experiments with 7B LLMs on the HH and TL;DR datasets substantiate the effectiveness of our method in both automatic metrics and human evaluation, thereby highlighting its potential for aligning LLMs with human intent and values

Bi-Directional Deep Contextual Video Compression

no code implementations16 Aug 2024 Xihua Sheng, Li Li, Dong Liu, Shiqi Wang

In this paper, we introduce a bi-directional deep contextual video compression scheme tailored for B-frames, termed DCVC-B, to improve the compression performance of deep B-frame coding.

Video Compression

High Efficiency Image Compression for Large Visual-Language Models

no code implementations24 Jul 2024 Binzhe Li, Shurun Wang, Shiqi Wang, Yan Ye

In this paper, we pioneer to propose a variable bitrate image compression framework consisting of a pre-editing module and an end-to-end codec to achieve promising rate-accuracy performance for different LVLMs.

Image Compression

DDR: Exploiting Deep Degradation Response as Flexible Image Descriptor

1 code implementation12 Jun 2024 Juncheng Wu, Zhangkai Ni, Hanli Wang, Wenhan Yang, Yuyin Zhou, Shiqi Wang

In this paper, we present Deep Degradation Response (DDR), a method to quantify changes in image deep features under varying degradation conditions.

Blind Image Quality Assessment Deblurring +3

Opinion-Unaware Blind Image Quality Assessment using Multi-Scale Deep Feature Statistics

1 code implementation29 May 2024 Zhangkai Ni, Yue Liu, Keyan Ding, Wenhan Yang, Hanli Wang, Shiqi Wang

To bridge these gaps, we propose integrating deep features from pre-trained visual models with a statistical analysis model into a Multi-scale Deep Feature Statistics (MDFS) model for achieving opinion-unaware BIQA (OU-BIQA), thereby eliminating the reliance on human rating data and significantly improving training efficiency.

Adaptive Image Quality Assessment via Teaching Large Multimodal Model to Compare

1 code implementation29 May 2024 Hanwei Zhu, HaoNing Wu, Yixuan Li, ZiCheng Zhang, Baoliang Chen, Lingyu Zhu, Yuming Fang, Guangtao Zhai, Weisi Lin, Shiqi Wang

Extensive experiments on nine IQA datasets validate that the Compare2Score effectively bridges text-defined comparative levels during training with converted single image quality score for inference, surpassing state-of-the-art IQA models across diverse scenarios.

Training LLMs to Better Self-Debug and Explain Code

no code implementations28 May 2024 Nan Jiang, Xiaopeng Li, Shiqi Wang, Qiang Zhou, Soneya Binta Hossain, Baishakhi Ray, Varun Kumar, Xiaofei Ma, Anoop Deoras

We thus propose an automated pipeline to collect a high-quality dataset for code explanation and refinement by generating a number of explanations and refinement trajectories and filtering via execution verification.

Code Generation Reinforcement Learning (RL)

Exposing AI-generated Videos: A Benchmark Dataset and a Local-and-Global Temporal Defect Based Detection Method

no code implementations7 May 2024 Peisong He, Leyao Zhu, Jiaxing Li, Shiqi Wang, Haoliang Li

The generative model has made significant advancements in the creation of realistic videos, which causes security issues.

Video Generation

Gradient-Congruity Guided Federated Sparse Training

no code implementations2 May 2024 Chris Xing Tian, Yibing Liu, Haoliang Li, Ray C. C. Cheung, Shiqi Wang

However, FL also faces challenges such as high computational and communication costs regarding resource-constrained devices, and poor generalization performance due to the heterogeneity of data across edge clients and the presence of out-of-distribution data.

Edge-computing Federated Learning

FakeBench: Probing Explainable Fake Image Detection via Large Multimodal Models

1 code implementation20 Apr 2024 Yixuan Li, Xuelin Liu, Xiaoyang Wang, Bu Sung Lee, Shiqi Wang, Anderson Rocha, Weisi Lin

Meanwhile, large multimodal models (LMMs) have exhibited immense visual-text capabilities on various tasks, bringing the potential for explainable fake image detection.

Binary Classification Fake Image Detection +1

CompGS: Efficient 3D Scene Representation via Compressed Gaussian Splatting

no code implementations15 Apr 2024 Xiangrui Liu, Xinju Wu, Pingping Zhang, Shiqi Wang, Zhu Li, Sam Kwong

Gaussian splatting, renowned for its exceptional rendering quality and efficiency, has emerged as a prominent technique in 3D scene representation.

CodeFort: Robust Training for Code Generation Models

no code implementations11 Apr 2024 Yuhao Zhang, Shiqi Wang, Haifeng Qian, Zijian Wang, Mingyue Shang, Linbo Liu, Sanjay Krishna Gouda, Baishakhi Ray, Murali Krishna Ramanathan, Xiaofei Ma, Anoop Deoras

Code generation models are not robust to small perturbations, which often lead to incorrect generations and significantly degrade the performance of these models.

Code Generation Contrastive Learning +1

PKU-DyMVHumans: A Multi-View Video Benchmark for High-Fidelity Dynamic Human Modeling

1 code implementation CVPR 2024 Xiaoyun Zheng, Liwei Liao, Xufeng Li, Jianbo Jiao, Rongjie Wang, Feng Gao, Shiqi Wang, Ronggang Wang

To facilitate the development of these fields, in this paper, we present PKU-DyMVHumans, a versatile human-centric dataset for high-fidelity reconstruction and rendering of dynamic human scenarios from dense multi-view videos.

Novel View Synthesis

Towards Open-ended Visual Quality Comparison

no code implementations26 Feb 2024 HaoNing Wu, Hanwei Zhu, ZiCheng Zhang, Erli Zhang, Chaofeng Chen, Liang Liao, Chunyi Li, Annan Wang, Wenxiu Sun, Qiong Yan, Xiaohong Liu, Guangtao Zhai, Shiqi Wang, Weisi Lin

Comparative settings (e. g. pairwise choice, listwise ranking) have been adopted by a wide range of subjective studies for image quality assessment (IQA), as it inherently standardizes the evaluation criteria across different observers and offer more clear-cut responses.

Image Quality Assessment

SPC-NeRF: Spatial Predictive Compression for Voxel Based Radiance Field

no code implementations26 Feb 2024 Zetian Song, Wenhong Duan, Yuhuai Zhang, Shiqi Wang, Siwei Ma, Wen Gao

Representing the Neural Radiance Field (NeRF) with the explicit voxel grid (EVG) is a promising direction for improving NeRFs.

Image Compression Neural Network Compression +1

ScreenAgent: A Vision Language Model-driven Computer Control Agent

1 code implementation9 Feb 2024 Runliang Niu, Jindong Li, Shiqi Wang, Yali Fu, Xiyu Hu, Xueyuan Leng, He Kong, Yi Chang, Qi Wang

Additionally, we construct the ScreenAgent Dataset, which collects screenshots and action sequences when completing a variety of daily computer tasks.

Language Modelling

Generative Visual Compression: A Review

no code implementations3 Feb 2024 Bolin Chen, Shanzhi Yin, Peilin Chen, Shiqi Wang, Yan Ye

Artificial Intelligence Generated Content (AIGC) is leading a new technical revolution for the acquisition of digital content and impelling the progress of visual compression towards competitive performance gains and diverse functionalities over traditional codecs.

Data Compression

2AFC Prompting of Large Multimodal Models for Image Quality Assessment

1 code implementation2 Feb 2024 Hanwei Zhu, Xiangjie Sui, Baoliang Chen, Xuelin Liu, Peilin Chen, Yuming Fang, Shiqi Wang

While abundant research has been conducted on improving high-level visual understanding and reasoning capabilities of large multimodal models~(LMMs), their visual quality assessment~(IQA) ability has been relatively under-explored.

Image Quality Assessment

Code-Aware Prompting: A study of Coverage Guided Test Generation in Regression Setting using LLM

no code implementations31 Jan 2024 Gabriel Ryan, Siddhartha Jain, Mingyue Shang, Shiqi Wang, Xiaofei Ma, Murali Krishna Ramanathan, Baishakhi Ray

Recent works using large language models (LLMs) for test generation have focused on improving generation quality through optimizing the test generation context and correcting errors in model outputs, but use fixed prompting strategies that prompt the model to generate tests without additional guidance.

software testing

Deep Shape-Texture Statistics for Completely Blind Image Quality Evaluation

no code implementations16 Jan 2024 Yixuan Li, Peilin Chen, Hanwei Zhu, Keyan Ding, Leida Li, Shiqi Wang

The perceptual quality is quantified by the variant Mahalanobis Distance between the inner and outer Shape-Texture Statistics (DSTS), wherein the inner and outer statistics respectively describe the quality fingerprints of the distorted image and natural images.

Blind Image Quality Assessment

CLIB-FIQA: Face Image Quality Assessment with Confidence Calibration

1 code implementation CVPR 2024 Fu-Zhao Ou, Chongyi Li, Shiqi Wang, Sam Kwong

Furthermore to alleviate the issue of the model placing excessive trust in inaccurate quality anchors we propose a confidence calibration method to correct the quality distribution by exploiting to the fullest extent of these objective quality factors characterized as the merged-factor distribution during training.

Face Image Quality Face Image Quality Assessment +1

Scalable Face Image Coding via StyleGAN Prior: Towards Compression for Human-Machine Collaborative Vision

no code implementations25 Dec 2023 Qi Mao, Chongyu Wang, Meng Wang, Shiqi Wang, Ruijie Chen, Libiao Jin, Siwei Ma

The accelerated proliferation of visual content and the rapid development of machine vision technologies bring significant challenges in delivering visual data on a gigantic scale, which shall be effectively represented to satisfy both human and machine requirements.

Image Compression

Generative Face Video Coding Techniques and Standardization Efforts: A Review

1 code implementation5 Nov 2023 Bolin Chen, Jie Chen, Shiqi Wang, Yan Ye

Generative Face Video Coding (GFVC) techniques can exploit the compact representation of facial priors and the strong inference capability of deep generative models, achieving high-quality face video communication in ultra-low bandwidth scenarios.

Semantic Face Compression for Metaverse: A Compact 3D Descriptor Based Approach

no code implementations24 Sep 2023 Binzhe Li, Bolin Chen, Zhao Wang, Shiqi Wang, Yan Ye

In this letter, we envision a new metaverse communication paradigm for virtual avatar faces, and develop the semantic face compression with compact 3D facial descriptors.

Perceptual Quality Assessment of 360$^\circ$ Images Based on Generative Scanpath Representation

1 code implementation7 Sep 2023 Xiangjie Sui, Hanwei Zhu, Xuelin Liu, Yuming Fang, Shiqi Wang, Zhou Wang

To address these issues, we introduce a unique generative scanpath representation (GSR) for effective quality inference of 360$^\circ$ images, which aggregates varied perceptual experiences of multi-hypothesis users under a predefined viewing condition.

Image Quality Assessment

Extreme Image Compression using Fine-tuned VQGANs

no code implementations17 Jul 2023 Qi Mao, Tinghan Yang, Yinuo Zhang, Zijian Wang, Meng Wang, Shiqi Wang, Siwei Ma

Remarkably, even with the loss of up to $20\%$ of indices, the images can be effectively restored with minimal perceptual loss.

Image Compression Quantization

Glow in the Dark: Low-Light Image Enhancement with External Memory

1 code implementation IEEE Transactions on Multimedia 2023 Dongjie Ye, Zhangkai Ni, Wenhan Yang, Hanli Wang, Shiqi Wang, Sam Kwong

Benefiting from the learned memory, more complex distributions of reference images in the entire dataset can be “remembered” to facilitate the adjustment of the testing samples more adaptively.

Low-Light Image Enhancement

Shifting Attention to Relevance: Towards the Predictive Uncertainty Quantification of Free-Form Large Language Models

2 code implementations3 Jul 2023 Jinhao Duan, Hao Cheng, Shiqi Wang, Alex Zavalny, Chenan Wang, Renjing Xu, Bhavya Kailkhura, Kaidi Xu

Large Language Models (LLMs) show promising results in language generation and instruction following but frequently "hallucinate", making their outputs less reliable.

Instruction Following Question Answering +4

The Age of Synthetic Realities: Challenges and Opportunities

no code implementations9 Jun 2023 João Phillipe Cardenuto, Jing Yang, Rafael Padilha, Renjie Wan, Daniel Moreira, Haoliang Li, Shiqi Wang, Fernanda Andaló, Sébastien Marcel, Anderson Rocha

Synthetic realities are digital creations or augmentations that are contextually generated through the use of Artificial Intelligence (AI) methods, leveraging extensive amounts of data to construct new narratives or realities, regardless of the intent to deceive.

Misinformation

Neuron Activation Coverage: Rethinking Out-of-distribution Detection and Generalization

1 code implementation5 Jun 2023 Yibing Liu, Chris Xing Tian, Haoliang Li, Lei Ma, Shiqi Wang

The out-of-distribution (OOD) problem generally arises when neural networks encounter data that significantly deviates from the training data distribution, i. e., in-distribution (InD).

Out-of-Distribution Detection

Geometric Prior Based Deep Human Point Cloud Geometry Compression

no code implementations2 May 2023 Xinju Wu, Pingping Zhang, Meng Wang, Peilin Chen, Shiqi Wang, Sam Kwong

The emergence of digital avatars has raised an exponential increase in the demand for human point clouds with realistic and intricate details.

Optimization-Inspired Cross-Attention Transformer for Compressive Sensing

1 code implementation CVPR 2023 Jiechong Song, Chong Mou, Shiqi Wang, Siwei Ma, Jian Zhang

And, PGCA block achieves an enhanced information interaction, which introduces the inertia force into the gradient descent step through a cross attention block.

Compressive Sensing

Perceptual Quality Assessment of Face Video Compression: A Benchmark and An Effective Method

1 code implementation14 Apr 2023 Yixuan Li, Bolin Chen, Baoliang Chen, Meng Wang, Shiqi Wang, Weisi Lin

In this paper, we introduce the large-scale Compressed Face Video Quality Assessment (CFVQA) database, which is the first attempt to systematically understand the perceptual quality and diversified compression distortions in face videos.

Video Compression Video Quality Assessment +1

Enhancing General Face Forgery Detection via Vision Transformer with Low-Rank Adaptation

no code implementations2 Mar 2023 Chenqi Kong, Haoliang Li, Shiqi Wang

Nowadays, forgery faces pose pressing security concerns over fake news, fraud, impersonation, etc.

Face Detection

Gap-closing Matters: Perceptual Quality Evaluation and Optimization of Low-Light Image Enhancement

1 code implementation22 Feb 2023 Baoliang Chen, Lingyu Zhu, Hanwei Zhu, Wenhan Yang, Linqi Song, Shiqi Wang

Subsequently, we propose an objective quality assessment measure that plays a critical role in bridging the gap between visual quality and enhancement.

Image Quality Assessment Low-Light Image Enhancement

Interactive Face Video Coding: A Generative Compression Framework

1 code implementation20 Feb 2023 Bolin Chen, Zhao Wang, Binzhe Li, Shurun Wang, Shiqi Wang, Yan Ye

In this paper, we propose a novel framework for Interactive Face Video Coding (IFVC), which allows humans to interact with the intrinsic visual representations instead of the signals.

Are Diffusion Models Vulnerable to Membership Inference Attacks?

2 code implementations2 Feb 2023 Jinhao Duan, Fei Kong, Shiqi Wang, Xiaoshuang Shi, Kaidi Xu

In this paper, we investigate the vulnerability of diffusion models to Membership Inference Attacks (MIAs), a common privacy concern.

Image Generation

M3FAS: An Accurate and Robust MultiModal Mobile Face Anti-Spoofing System

1 code implementation30 Jan 2023 Chenqi Kong, Kexin Zheng, Yibing Liu, Shiqi Wang, Anderson Rocha, Haoliang Li

Face presentation attacks (FPA), also known as face spoofing, have brought increasing concerns to the public through various malicious applications, such as financial fraud and privacy leakage.

Face Anti-Spoofing Face Recognition

Troubleshooting Ethnic Quality Bias with Curriculum Domain Adaptation for Face Image Quality Assessment

1 code implementation ICCV 2023 Fu-Zhao Ou, Baoliang Chen, Chongyi Li, Shiqi Wang, Sam Kwong

Furthermore, we design an easy-to-hard training scheduler based on the inter-domain uncertainty and intra-domain quality margin as well as the ranking-based domain adversarial network to enhance the effectiveness of transfer learning and further reduce the source risk in domain adaptation.

Domain Adaptation Face Image Quality +4

ReCode: Robustness Evaluation of Code Generation Models

2 code implementations20 Dec 2022 Shiqi Wang, Zheng Li, Haifeng Qian, Chenghao Yang, Zijian Wang, Mingyue Shang, Varun Kumar, Samson Tan, Baishakhi Ray, Parminder Bhatia, Ramesh Nallapati, Murali Krishna Ramanathan, Dan Roth, Bing Xiang

Most existing works on robustness in text or code tasks have focused on classification, while robustness in generation tasks is an uncharted area and to date there is no comprehensive benchmark for robustness in code generation.

Code Generation HumanEval

Two-branch Multi-scale Deep Neural Network for Generalized Document Recapture Attack Detection

1 code implementation30 Nov 2022 Jiaxing Li, Chenqi Kong, Shiqi Wang, Haoliang Li

The image recapture attack is an effective image manipulation method to erase certain forensic traces, and when targeting on personal document images, it poses a great threat to the security of e-commerce and other web applications.

Image Manipulation

Generalization Beyond Feature Alignment: Concept Activation-Guided Contrastive Learning

no code implementations13 Nov 2022 Yibing Liu, Chris Xing Tian, Haoliang Li, Shiqi Wang

Specifically, by treating feature elements as neuron activation states, we show that conventional alignment methods tend to deteriorate the diversity of learned invariant features, as they indiscriminately minimize all neuron activation differences.

Contrastive Learning Diversity +1

DeepDC: Deep Distance Correlation as a Perceptual Image Quality Evaluator

1 code implementation9 Nov 2022 Hanwei Zhu, Baoliang Chen, Lingyu Zhu, Shiqi Wang, Weisi Lin

ImageNet pre-trained deep neural networks (DNNs) show notable transferability for building effective image quality assessment (IQA) models.

Attribute Image Quality Assessment +2

Multi-lingual Evaluation of Code Generation Models

2 code implementations26 Oct 2022 Ben Athiwaratkun, Sanjay Krishna Gouda, Zijian Wang, Xiaopeng Li, Yuchen Tian, Ming Tan, Wasi Uddin Ahmad, Shiqi Wang, Qing Sun, Mingyue Shang, Sujan Kumar Gonugondla, Hantian Ding, Varun Kumar, Nathan Fulton, Arash Farahani, Siddhartha Jain, Robert Giaquinto, Haifeng Qian, Murali Krishna Ramanathan, Ramesh Nallapati, Baishakhi Ray, Parminder Bhatia, Sudipta Sengupta, Dan Roth, Bing Xiang

Using these benchmarks, we are able to assess the performance of code generation models in a multi-lingual fashion, and discovered generalization ability of language models on out-of-domain languages, advantages of multi-lingual models over mono-lingual, the ability of few-shot prompting to teach the model new languages, and zero-shot translation abilities even on mono-lingual settings.

Code Completion Code Translation +2

Digital and Physical Face Attacks: Reviewing and One Step Further

no code implementations29 Sep 2022 Chenqi Kong, Shiqi Wang, Haoliang Li

With the rapid progress over the past five years, face authentication has become the most pervasive biometric recognition method.

Face Recognition

Learning from Mixed Datasets: A Monotonic Image Quality Assessment Model

1 code implementation21 Sep 2022 Zhaopeng Feng, Keyang Zhang, Shuyue Jia, Baoliang Chen, Shiqi Wang

Deep learning based image quality assessment (IQA) models usually learn to predict image quality from a single dataset, leading the model to overfit specific scenes.

Image Quality Assessment

Just Noticeable Difference Modeling for Face Recognition System

no code implementations13 Sep 2022 Yu Tian, Zhangkai Ni, Baoliang Chen, Shurun Wang, Shiqi Wang, Hanli Wang, Sam Kwong

In particular, in order to maximum redundancy removal without impairment of robust identity information, we apply the encoder with multiple feature extraction and attention-based feature decomposition modules to progressively decompose face features into two uncorrelated components, i. e., identity and residual features, via self-supervised learning.

Face Recognition Self-Supervised Learning

Deep Feature Statistics Mapping for Generalized Screen Content Image Quality Assessment

1 code implementation12 Sep 2022 Baoliang Chen, Hanwei Zhu, Lingyu Zhu, Shiqi Wang, Sam Kwong

The underlying mechanism of the proposed approach is based upon the mild assumption that the SCIs, which are not physically acquired, still obey certain statistics that could be understood in a learning fashion.

A Weakly Supervised Learning Framework for Salient Object Detection via Hybrid Labels

3 code implementations7 Sep 2022 Runmin Cong, Qi Qin, Chen Zhang, Qiuping Jiang, Shiqi Wang, Yao Zhao, Sam Kwong

In this paper, we focus on a new weakly-supervised SOD task under hybrid labels, where the supervision labels include a large number of coarse labels generated by the traditional unsupervised method and a small number of real labels.

object-detection RGB Salient Object Detection +3

High Dynamic Range Image Quality Assessment Based on Frequency Disparity

1 code implementation6 Sep 2022 Yue Liu, Zhangkai Ni, Shiqi Wang, Hanli Wang, Sam Kwong

In this paper, a novel and effective image quality assessment (IQA) algorithm based on frequency disparity for high dynamic range (HDR) images is proposed, termed as local-global frequency feature-based model (LGFM).

Image Quality Assessment Vocal Bursts Intensity Prediction

General Cutting Planes for Bound-Propagation-Based Neural Network Verification

3 code implementations11 Aug 2022 huan zhang, Shiqi Wang, Kaidi Xu, Linyi Li, Bo Li, Suman Jana, Cho-Jui Hsieh, J. Zico Kolter

Our generalized bound propagation method, GCP-CROWN, opens up the opportunity to apply general cutting plane methods for neural network verification while benefiting from the efficiency and GPU acceleration of bound propagation methods.

DeepWSD: Projecting Degradations in Perceptual Space to Wasserstein Distance in Deep Feature Space

1 code implementation5 Aug 2022 Xigran Liao, Baoliang Chen, Hanwei Zhu, Shiqi Wang, Mingliang Zhou, Sam Kwong

Existing deep learning-based full-reference IQA (FR-IQA) models usually predict the image quality in a deterministic way by explicitly comparing the features, gauging how severely distorted an image is by how far the corresponding feature lies from the space of the reference images.

Cycle-Interactive Generative Adversarial Network for Robust Unsupervised Low-Light Enhancement

no code implementations3 Jul 2022 Zhangkai Ni, Wenhan Yang, Hanli Wang, Shiqi Wang, Lin Ma, Sam Kwong

Getting rid of the fundamental limitations in fitting to the paired training data, recent unsupervised low-light enhancement methods excel in adjusting illumination and contrast of images.

Generative Adversarial Network Low-Light Image Enhancement

Generalizing to Evolving Domains with Latent Structure-Aware Sequential Autoencoder

1 code implementation16 May 2022 Tiexin Qin, Shiqi Wang, Haoliang Li

Domain generalization aims to improve the generalization capability of machine learning systems to out-of-distribution (OOD) data.

Evolving Domain Generalization

CIRS: Bursting Filter Bubbles by Counterfactual Interactive Recommender System

1 code implementation4 Apr 2022 Chongming Gao, Shiqi Wang, Shijun Li, Jiawei Chen, Xiangnan He, Wenqiang Lei, Biao Li, Yuan Zhang, Peng Jiang

The basic idea is to first learn a causal user model on historical data to capture the overexposure effect of items on user satisfaction.

Causal Inference counterfactual +2

The Loop Game: Quality Assessment and Optimization for Low-Light Image Enhancement

no code implementations20 Feb 2022 Baoliang Chen, Lingyu Zhu, Hanwei Zhu, Wenhan Yang, Fangbo Lu, Shiqi Wang

In particular, we create a large-scale database for QUality assessment Of The Enhanced LOw-Light Image (QUOTE-LOL), which serves as the foundation in studying and developing objective quality assessment measures.

Low-Light Image Enhancement

Distortion-Aware Loop Filtering of Intra 360^o Video Coding with Equirectangular Projection

no code implementations20 Feb 2022 Pingping Zhang, Xu Wang, Linwei Zhu, Yun Zhang, Shiqi Wang, Sam Kwong

In this paper, we propose a distortion-aware loop filtering model to improve the performance of intra coding for 360$^o$ videos projected via equirectangular projection (ERP) format.

ERP Image Reconstruction

Who Are the Best Adopters? User Selection Model for Free Trial Item Promotion

no code implementations19 Feb 2022 Shiqi Wang, Chongming Gao, Min Gao, Junliang Yu, Zongwei Wang, Hongzhi Yin

By providing users with opportunities to experience goods without charge, a free trial makes adopters know more about products and thus encourages their willingness to buy.

Marketing reinforcement-learning +2

Generalized Visual Quality Assessment of GAN-Generated Face Images

no code implementations28 Jan 2022 Yu Tian, Zhangkai Ni, Baoliang Chen, Shiqi Wang, Hanli Wang, Sam Kwong

However, little work has been dedicated to automatic quality assessment of such GAN-generated face images (GFIs), even less have been devoted to generalized and robust quality assessment of GFIs generated with unseen GAN model.

Face Generation Image Quality Assessment +1

CSformer: Bridging Convolution and Transformer for Compressive Sensing

1 code implementation31 Dec 2021 Dongjie Ye, Zhangkai Ni, Hanli Wang, Jian Zhang, Shiqi Wang, Sam Kwong

The proposed approach is an end-to-end compressive image sensing method, composed of adaptive sampling and recovery.

Compressive Sensing Inductive Bias +1

Locally Adaptive Structure and Texture Similarity for Image Quality Assessment

no code implementations16 Oct 2021 Keyan Ding, Yi Liu, Xueyi Zou, Shiqi Wang, Kede Ma

The latest advances in full-reference image quality assessment (IQA) involve unifying structure and texture similarity based on deep representations.

Full-Reference Image Quality Assessment Image Super-Resolution +1

A Branch and Bound Framework for Stronger Adversarial Attacks of ReLU Networks

no code implementations29 Sep 2021 huan zhang, Shiqi Wang, Kaidi Xu, Yihan Wang, Suman Jana, Cho-Jui Hsieh, J Zico Kolter

In this work, we formulate an adversarial attack using a branch-and-bound (BaB) procedure on ReLU neural networks and search adversarial examples in the activation space corresponding to binary variables in a mixed integer programming (MIP) formulation.

Adversarial Attack

Towards Top-Down Just Noticeable Difference Estimation of Natural Images

1 code implementation11 Aug 2021 Qiuping Jiang, Zhentao Liu, Shiqi Wang, Feng Shao, Weisi Lin

Instead of explicitly formulating and fusing different masking effects in a bottom-up way, the proposed JND estimation model dedicates to first predicting a critical perceptual lossless (CPL) counterpart of the original image and then calculating the difference map between the original image and the predicted CPL image as the JND map.

Image Compression Image Reconstruction +1

No-Reference Image Quality Assessment by Hallucinating Pristine Features

1 code implementation9 Aug 2021 Baoliang Chen, Lingyu Zhu, Chenqi Kong, Hanwei Zhu, Shiqi Wang, Zhu Li

In this paper, we propose a no-reference (NR) image quality assessment (IQA) method via feature level pseudo-reference (PR) hallucination.

Disentanglement Hallucination +2

Detect and Locate: Exposing Face Manipulation by Semantic- and Noise-level Telltales

1 code implementation13 Jul 2021 Chenqi Kong, Baoliang Chen, Haoliang Li, Shiqi Wang, Anderson Rocha, Sam Kwong

The technological advancements of deep learning have enabled sophisticated face manipulation schemes, raising severe trust issues and security concerns in modern society.

Decision Making

End-to-end Compression Towards Machine Vision: Network Architecture Design and Optimization

no code implementations1 Jul 2021 Shurun Wang, Zhao Wang, Shiqi Wang, Yan Ye

In this paper, we show that the design and optimization of network architecture could be further improved for compression towards machine vision.

object-detection Object Detection

Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Neural Network Robustness Verification

no code implementations NeurIPS 2021 Shiqi Wang, huan zhang, Kaidi Xu, Xue Lin, Suman Jana, Cho-Jui Hsieh, J Zico Kolter

We develop $\beta$-CROWN, a new bound propagation based method that can fully encode neuron split constraints in branch-and-bound (BaB) based complete verification via optimizable parameters $\beta$.

Learning Security Classifiers with Verified Global Robustness Properties

1 code implementation24 May 2021 Yizheng Chen, Shiqi Wang, Yue Qin, Xiaojing Liao, Suman Jana, David Wagner

Since data distribution shift is very common in security applications, e. g., often observed for malware detection, local robustness cannot guarantee that the property holds for unseen inputs at the time of deploying the classifier.

Malware Detection

Privacy-Preserving Constrained Domain Generalization via Gradient Alignment

no code implementations14 May 2021 Chris Xing Tian, Haoliang Li, YuFei Wang, Shiqi Wang

However, due to the issue of limited dataset availability and the strict legal and ethical requirements for patient privacy protection, the broad applications of medical imaging classification driven by DNN with large-scale training data have been largely hindered.

Domain Generalization Federated Learning +3

Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Complete and Incomplete Neural Network Robustness Verification

5 code implementations NeurIPS 2021 Shiqi Wang, huan zhang, Kaidi Xu, Xue Lin, Suman Jana, Cho-Jui Hsieh, J. Zico Kolter

Compared to the typically tightest but very costly semidefinite programming (SDP) based incomplete verifiers, we obtain higher verified accuracy with three orders of magnitudes less verification time.

Adversarial Attack

Neuron Coverage-Guided Domain Generalization

no code implementations27 Feb 2021 Chris Xing Tian, Haoliang Li, Xiaofei Xie, Yang Liu, Shiqi Wang

More specifically, by treating the DNN as a program and each neuron as a functional point of the code, during the network training we aim to improve the generalization capability by maximizing the neuron coverage of DNN with the gradient similarity regularization between the original and augmented samples.

DNN Testing Domain Generalization

Camera Invariant Feature Learning for Generalized Face Anti-spoofing

no code implementations25 Jan 2021 Baoliang Chen, Wenhan Yang, Haoliang Li, Shiqi Wang, Sam Kwong

The first branch aims to learn the camera invariant spoofing features via feature level decomposition in the high frequency domain.

Face Anti-Spoofing

Towards Unsupervised Deep Image Enhancement with Generative Adversarial Network

1 code implementation30 Dec 2020 Zhangkai Ni, Wenhan Yang, Shiqi Wang, Lin Ma, Sam Kwong

In this paper, we present an unsupervised image enhancement generative adversarial network (UEGAN), which learns the corresponding image-to-image mapping from a set of images with desired characteristics in an unsupervised manner, rather than learning on a large number of paired images.

Generative Adversarial Network Image Enhancement +1

Unpaired Image Enhancement with Quality-Attention Generative Adversarial Network

no code implementations30 Dec 2020 Zhangkai Ni, Wenhan Yang, Shiqi Wang, Lin Ma, Sam Kwong

The key novelty of the proposed QAGAN lies in the injected QAM for the generator such that it learns domain-relevant quality attention directly from the two domains.

Generative Adversarial Network Image Enhancement

Learning Generalized Spatial-Temporal Deep Feature Representation for No-Reference Video Quality Assessment

1 code implementation27 Dec 2020 Baoliang Chen, Lingyu Zhu, Guo Li, Hongfei Fan, Shiqi Wang

In this work, we propose a no-reference video quality assessment method, aiming to achieve high-generalization capability in cross-content, -resolution and -frame rate quality prediction.

Video Quality Assessment

Adaptive Verifiable Training Using Pairwise Class Similarity

no code implementations14 Dec 2020 Shiqi Wang, Kevin Eykholt, Taesung Lee, Jiyong Jang, Ian Molloy

On CIFAR10, a non-robust LeNet model has a 21. 63% error rate, while a model created using verifiable training and a L-infinity robustness criterion of 8/255, has an error rate of 57. 10%.

Attribute

Conceptual Compression via Deep Structure and Texture Synthesis

2 code implementations10 Nov 2020 Jianhui Chang, Zhenghui Zhao, Chuanmin Jia, Shiqi Wang, Lingbo Yang, Qi Mao, Jian Zhang, Siwei Ma

To this end, we propose a novel conceptual compression framework that encodes visual data into compact structure and texture representations, then decodes in a deep synthesis fashion, aiming to achieve better visual reconstruction quality, flexible content manipulation, and potential support for various vision tasks.

Texture Synthesis

DRL-FAS: A Novel Framework Based on Deep Reinforcement Learning for Face Anti-Spoofing

no code implementations16 Sep 2020 Rizhao Cai, Haoliang Li, Shiqi Wang, Changsheng chen, Alex ChiChung Kot

Inspired by the philosophy employed by human beings to determine whether a presented face example is genuine or not, i. e., to glance at the example globally first and then carefully observe the local regions to gain more discriminative information, for the face anti-spoofing problem, we propose a novel framework based on the Convolutional Neural Network (CNN) and the Recurrent Neural Network (RNN).

Deep Reinforcement Learning Face Anti-Spoofing +2

Light Can Hack Your Face! Black-box Backdoor Attack on Face Recognition Systems

no code implementations15 Sep 2020 Haoliang Li, Yufei Wang, Xiaofei Xie, Yang Liu, Shiqi Wang, Renjie Wan, Lap-Pui Chau, Alex C. Kot

In this paper, we propose a novel black-box backdoor attack technique on face recognition systems, which can be conducted without the knowledge of the targeted DNN model.

Backdoor Attack Face Recognition

No-reference Screen Content Image Quality Assessment with Unsupervised Domain Adaptation

no code implementations19 Aug 2020 Baoliang Chen, Haoliang Li, Hongfei Fan, Shiqi Wang

Here, we develop the first unsupervised domain adaptation based no reference quality assessment method for SCIs, leveraging rich subjective ratings of the natural images (NIs).

Diversity Image Quality Assessment +3

Towards Modality Transferable Visual Information Representation with Optimal Model Compression

no code implementations13 Aug 2020 Rongqun Lin, Linwei Zhu, Shiqi Wang, Sam Kwong

Compactly representing the visual signals is of fundamental importance in various image/video-centered applications.

Model Compression Philosophy

Towards Understanding Fast Adversarial Training

no code implementations4 Jun 2020 Bai Li, Shiqi Wang, Suman Jana, Lawrence Carin

Current neural-network-based classifiers are susceptible to adversarial examples.

Iterative Network for Image Super-Resolution

1 code implementation20 May 2020 Yuqing Liu, Shiqi Wang, Jian Zhang, Shanshe Wang, Siwei Ma, Wen Gao

A novel iterative super-resolution network (ISRN) is proposed on top of the iterative optimization.

Image Super-Resolution SSIM

Comparison of Image Quality Models for Optimization of Image Processing Systems

1 code implementation4 May 2020 Keyan Ding, Kede Ma, Shiqi Wang, Eero P. Simoncelli

The performance of objective image quality assessment (IQA) models has been evaluated primarily by comparing model predictions to human quality judgments.

Deblurring Denoising +2

Towards Analysis-friendly Face Representation with Scalable Feature and Texture Compression

no code implementations21 Apr 2020 Shurun Wang, Shiqi Wang, Wenhan Yang, Xinfeng Zhang, Shanshe Wang, Siwei Ma, Wen Gao

In particular, we study the feature and texture compression in a scalable coding framework, where the base layer serves as the deep learning feature and enhancement layer targets to perfectly reconstruct the texture.

Image Compression

Image Quality Assessment: Unifying Structure and Texture Similarity

2 code implementations16 Apr 2020 Keyan Ding, Kede Ma, Shiqi Wang, Eero P. Simoncelli

Objective measures of image quality generally operate by comparing pixels of a "degraded" image to those of the original.

Image Quality Assessment Retrieval +1

Towards Practical Lottery Ticket Hypothesis for Adversarial Training

1 code implementation6 Mar 2020 Bai Li, Shiqi Wang, Yunhan Jia, Yantao Lu, Zhenyu Zhong, Lawrence Carin, Suman Jana

Recent research has proposed the lottery ticket hypothesis, suggesting that for a deep neural network, there exist trainable sub-networks performing equally or better than the original model with commensurate training steps.

HYDRA: Pruning Adversarially Robust Neural Networks

4 code implementations NeurIPS 2020 Vikash Sehwag, Shiqi Wang, Prateek Mittal, Suman Jana

We demonstrate that our approach, titled HYDRA, achieves compressed networks with state-of-the-art benign and robust accuracy, simultaneously.

Network Pruning

ARMA Nets: Expanding Receptive Field for Dense Prediction

1 code implementation NeurIPS 2020 Jiahao Su, Shiqi Wang, Furong Huang

In this work, we propose to replace any traditional convolutional layer with an autoregressive moving-average (ARMA) layer, a novel module with an adjustable receptive field controlled by the learnable autoregressive coefficients.

Image Classification Semantic Segmentation +1

End-to-End Facial Deep Learning Feature Compression with Teacher-Student Enhancement

no code implementations10 Feb 2020 Shurun Wang, Wenhan Yang, Shiqi Wang

In this paper, we propose a novel end-to-end feature compression scheme by leveraging the representation and learning capability of deep neural networks, towards intelligent front-end equipped analysis with promising accuracy and efficiency.

Feature Compression

Single Image Deraining: From Model-Based to Data-Driven and Beyond

no code implementations16 Dec 2019 Wenhan Yang, Robby T. Tan, Shiqi Wang, Yuming Fang, Jiaying Liu

The goal of single-image deraining is to restore the rain-free background scenes of an image degraded by rain streaks and rain accumulation.

Single Image Deraining

Cost-Aware Robust Tree Ensembles for Security Applications

2 code implementations3 Dec 2019 Yizheng Chen, Shiqi Wang, Weifan Jiang, Asaf Cidon, Suman Jana

There are various costs for attackers to manipulate the features of security classifiers.

Spam detection

Towards Digital Retina in Smart Cities: A Model Generation, Utilization and Communication Paradigm

1 code implementation31 Jul 2019 Yihang Lou, Ling-Yu Duan, Yong Luo, Ziqian Chen, Tongliang Liu, Shiqi Wang, Wen Gao

The digital retina in smart cities is to select what the City Eye tells the City Brain, and convert the acquired visual data from front-end visual sensors to features in an intelligent sensing manner.

Deep Learning

Intrinsic Image Popularity Assessment

1 code implementation3 Jul 2019 Keyan Ding, Kede Ma, Shiqi Wang

The goal of research in automatic image popularity assessment (IPA) is to develop computational models that can accurately predict the potential of a social image to go viral on the Internet.

Image popularity prediction

Towards Compact and Robust Deep Neural Networks

no code implementations14 Jun 2019 Vikash Sehwag, Shiqi Wang, Prateek Mittal, Suman Jana

In this work, we rigorously study the extension of network pruning strategies to preserve both benign accuracy and robustness of a network.

Adversarial Robustness Network Pruning

Enhancing Gradient-based Attacks with Symbolic Intervals

no code implementations5 Jun 2019 Shiqi Wang, Yizheng Chen, Ahmed Abdou, Suman Jana

In this paper, we present interval attacks, a new technique to find adversarial examples to evaluate the robustness of neural networks.

Open-Ended Question Answering

Masked Non-Autoregressive Image Captioning

no code implementations3 Jun 2019 Junlong Gao, Xi Meng, Shiqi Wang, Xia Li, Shanshe Wang, Siwei Ma, Wen Gao

Existing captioning models often adopt the encoder-decoder architecture, where the decoder uses autoregressive decoding to generate captions, such that each token is generated sequentially given the preceding generated tokens.

Decoder Diversity +3

On the Mathematical Understanding of ResNet with Feynman Path Integral

no code implementations16 Apr 2019 Minghao Yin, Xiu Li, Yongbing Zhang, Shiqi Wang

In this paper, we aim to understand Residual Network (ResNet) in a scientifically sound way by providing a bridge between ResNet and Feynman path integral.

Self-critical n-step Training for Image Captioning

no code implementations CVPR 2019 Junlong Gao, Shiqi Wang, Shanshe Wang, Siwei Ma, Wen Gao

Existing methods for image captioning are usually trained by cross entropy loss, which leads to exposure bias and the inconsistency between the optimizing function and evaluation metrics.

Image Captioning Reinforcement Learning

Image and Video Compression with Neural Networks: A Review

no code implementations7 Apr 2019 Siwei Ma, Xinfeng Zhang, Chuanmin Jia, Zhenghui Zhao, Shiqi Wang, Shanshe Wang

Deep convolution neural network (CNN) which makes the neural network resurge in recent years and has achieved great success in both artificial intelligent and signal processing fields, also provides a novel and promising solution for image and video compression.

Video Compression

On Training Robust PDF Malware Classifiers

1 code implementation6 Apr 2019 Yizheng Chen, Shiqi Wang, Dongdong She, Suman Jana

A practically useful malware classifier must be robust against evasion attacks.

Scalable Facial Image Compression with Deep Feature Reconstruction

no code implementations14 Mar 2019 Shurun Wang, Shiqi Wang, Xinfeng Zhang, Shanshe Wang, Siwei Ma, Wen Gao

In this paper, we propose a scalable image compression scheme, including the base layer for feature representation and enhancement layer for texture representation.

Image Compression

MixTrain: Scalable Training of Verifiably Robust Neural Networks

1 code implementation6 Nov 2018 Shiqi Wang, Yizheng Chen, Ahmed Abdou, Suman Jana

Making neural networks robust against adversarial inputs has resulted in an arms race between new defenses and attacks.

Efficient Formal Safety Analysis of Neural Networks

2 code implementations NeurIPS 2018 Shiqi Wang, Kexin Pei, Justin Whitehouse, Junfeng Yang, Suman Jana

Our approach can check different safety properties and find concrete counterexamples for networks that are 10$\times$ larger than the ones supported by existing analysis techniques.

Adversarial Attack Adversarial Defense +3

Intermediate Deep Feature Compression: the Next Battlefield of Intelligent Sensing

no code implementations17 Sep 2018 Zhuo Chen, Weisi Lin, Shiqi Wang, Ling-Yu Duan, Alex C. Kot

The recent advances of hardware technology have made the intelligent analysis equipped at the front-end with deep learning more prevailing and practical.

Data Compression Deep Learning +1

Domain Generalization With Adversarial Feature Learning

no code implementations CVPR 2018 Haoliang Li, Sinno Jialin Pan, Shiqi Wang, Alex C. Kot

In this paper, we tackle the problem of domain generalization: how to learn a generalized feature representation for an “unseen” target domain by taking the advantage of multiple seen source-domain data.

Domain Generalization

Formal Security Analysis of Neural Networks using Symbolic Intervals

3 code implementations28 Apr 2018 Shiqi Wang, Kexin Pei, Justin Whitehouse, Junfeng Yang, Suman Jana

In this paper, we present a new direction for formally checking security properties of DNNs without using SMT solvers.

Autonomous Vehicles Collision Avoidance

AI Oriented Large-Scale Video Management for Smart City: Technologies, Standards and Beyond

no code implementations5 Dec 2017 Ling-Yu Duan, Yihang Lou, Shiqi Wang, Wen Gao, Yong Rui

To practically facilitate deep neural network models in the large-scale video analysis, there are still unprecedented challenges for the large-scale video data management.

Deep Learning Management

Spatial-Temporal Residue Network Based In-Loop Filter for Video Coding

no code implementations25 Sep 2017 Chuanmin Jia, Shiqi Wang, Xinfeng Zhang, Shanshe Wang, Siwei Ma

Deep learning has demonstrated tremendous break through in the area of image/video processing.

Multimedia

Image Quality Assessment Guided Deep Neural Networks Training

3 code implementations13 Aug 2017 Zhuo Chen, Weisi Lin, Shiqi Wang, Long Xu, Leida Li

For many computer vision problems, the deep neural networks are trained and validated based on the assumption that the input images are pristine (i. e., artifact-free).

Data Augmentation Image Classification +1

Compact Descriptors for Video Analysis: the Emerging MPEG Standard

no code implementations26 Apr 2017 Ling-Yu Duan, Vijay Chandrasekhar, Shiqi Wang, Yihang Lou, Jie Lin, Yan Bai, Tiejun Huang, Alex ChiChung Kot, Wen Gao

This paper provides an overview of the on-going compact descriptors for video analysis standard (CDVA) from the ISO/IEC moving pictures experts group (MPEG).

Improving Object Detection with Region Similarity Learning

no code implementations1 Mar 2017 Feng Gao, Yihang Lou, Yan Bai, Shiqi Wang, Tiejun Huang, Ling-Yu Duan

Object detection aims to identify instances of semantic objects of a certain class in images or videos.

Multi-Task Learning Object +3

Incorporating Intra-Class Variance to Fine-Grained Visual Recognition

no code implementations1 Mar 2017 Yan Bai, Feng Gao, Yihang Lou, Shiqi Wang, Tiejun Huang, Ling-Yu Duan

In this paper, we propose to leverage intra-class variance in metric learning of triplet network to improve the performance of fine-grained recognition.

Fine-Grained Visual Recognition Metric Learning +2

Globally Variance-Constrained Sparse Representation and Its Application in Image Set Coding

no code implementations17 Aug 2016 Xiang Zhang, Jiarui Sun, Siwei Ma, Zhouchen Lin, Jian Zhang, Shiqi Wang, Wen Gao

Therefore, introducing an accurate rate-constraint in sparse coding and dictionary learning becomes meaningful, which has not been fully exploited in the context of sparse representation.

Data Compression Dictionary Learning

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