Search Results for author: Zixuan Chen

Found 18 papers, 7 papers with code

Layered Neighborhood Expansion for Incremental Multiple Graph Matching

1 code implementation ECCV 2020 Zixuan Chen, Zhihui Xie, Junchi Yan Yinqiang Zheng, Xiaokang Yang

In this paper, we treat the graphs as graphs on a super-graph, and propose a novel breadth first search based method for expanding the neighborhood on the super-graph for a new coming graph, such that the matching with the new graph can be efficiently performed within the constructed neighborhood.

Graph Matching

Visual Whole-Body Control for Legged Loco-Manipulation

no code implementations25 Mar 2024 Minghuan Liu, Zixuan Chen, Xuxin Cheng, Yandong Ji, Ri-Zhao Qiu, Ruihan Yang, Xiaolong Wang

We propose a framework that can conduct the whole-body control autonomously with visual observations.


HITSnDIFFs: From Truth Discovery to Ability Discovery by Recovering Matrices with the Consecutive Ones Property

1 code implementation21 Dec 2023 Zixuan Chen, Subhodeep Mitra, R Ravi, Wolfgang Gatterbauer

We call this problem "ability discovery" to emphasize the connection to and duality with the more well-studied problem of "truth discovery".

A New Baseline Assumption of Integated Gradients Based on Shaply value

no code implementations7 Oct 2023 Shuyang Liu, Zixuan Chen, Ge Shi, Ji Wang, Changjie Fan, Yu Xiong, Runze Wu Yujing Hu, Ze Ji, Yang Gao

The selection of appropriate baselines in IG is crucial for crafting meaningful and unbiased explanations of model predictions in diverse settings.

Prompt-based test-time real image dehazing: a novel pipeline

1 code implementation29 Sep 2023 Zixuan Chen, Zewei He, Ziqian Lu, Xuecheng Sun, Zhe-Ming Lu

We experimentally find that given a dehazing model trained on synthetic data, by fine-tuning the statistics (i. e., mean and standard deviation) of encoding features, PTTD is able to narrow the domain gap, boosting the performance of real image dehazing.

Image Dehazing

Accurate and lightweight dehazing via multi-receptive-field non-local network and novel contrastive regularization

no code implementations28 Sep 2023 Zewei He, Zixuan Chen, Ziqian Lu, Xuecheng Sun, Zhe-Ming Lu

Thus, a multi-receptive-field non-local network (MRFNLN) consisting of the multi-stream feature attention block (MSFAB) and cross non-local block (CNLB) is presented in this paper.

Image Dehazing

CasIL: Cognizing and Imitating Skills via a Dual Cognition-Action Architecture

no code implementations28 Sep 2023 Zixuan Chen, Ze Ji, Shuyang Liu, Jing Huo, Yiyu Chen, Yang Gao

Heuristically, we extend the usual notion of action to a dual Cognition (high-level)-Action (low-level) architecture by introducing intuitive human cognitive priors, and propose a novel skill IL framework through human-robot interaction, called Cognition-Action-based Skill Imitation Learning (CasIL), for the robotic agent to effectively cognize and imitate the critical skills from raw visual demonstrations.

Imitation Learning

APRF: Anti-Aliasing Projection Representation Field for Inverse Problem in Imaging

no code implementations11 Jul 2023 Zixuan Chen, Lingxiao Yang, JianHuang Lai, Xiaohua Xie

However, these methods have not considered the correlation between adjacent projection views, resulting in aliasing artifacts on SV sinograms.

OSP: Boosting Distributed Model Training with 2-stage Synchronization

no code implementations29 Jun 2023 Zixuan Chen, Lei Shi, Xuandong Liu, Jiahui Li, Sen Liu, Yang Xu

However, these two types of methods can result in accuracy loss due to discarded gradients and have limited enhancement on the throughput of model synchronization, respectively.

CuNeRF: Cube-Based Neural Radiance Field for Zero-Shot Medical Image Arbitrary-Scale Super Resolution

1 code implementation ICCV 2023 Zixuan Chen, Jian-Huang Lai, Lingxiao Yang, Xiaohua Xie

Medical image arbitrary-scale super-resolution (MIASSR) has recently gained widespread attention, aiming to super sample medical volumes at arbitrary scales via a single model.

Computed Tomography (CT) Super-Resolution

Hard Nominal Example-aware Template Mutual Matching for Industrial Anomaly Detection

no code implementations28 Mar 2023 Zixuan Chen, Xiaohua Xie, Lingxiao Yang, JianHuang Lai

Additionally, to meet the speed-accuracy demands, we further propose \textbf{P}ixel-level \textbf{T}emplate \textbf{S}election (PTS) to streamline the original template set.

Anomaly Detection Incremental Learning

DEA-Net: Single image dehazing based on detail-enhanced convolution and content-guided attention

1 code implementation12 Jan 2023 Zixuan Chen, Zewei He, Zhe-Ming Lu

In this paper, a detail-enhanced attention block (DEAB) consisting of the detail-enhanced convolution (DEConv) and the content-guided attention (CGA) is proposed to boost the feature learning for improving the dehazing performance.

Image Dehazing

3D-VFD: A Victim-free Detector against 3D Adversarial Point Clouds

no code implementations18 May 2022 Jiahao Zhu, Huajun Zhou, Zixuan Chen, Yi Zhou, Xiaohua Xie

3D deep models consuming point clouds have achieved sound application effects in computer vision.

Adversarial Attack Steganalysis

Semantic Segmentation on VSPW Dataset through Aggregation of Transformer Models

no code implementations3 Sep 2021 Zixuan Chen, Junhong Zou, Xiaotao Wang

Semantic segmentation is an important task in computer vision, from which some important usage scenarios are derived, such as autonomous driving, scene parsing, etc.

Autonomous Driving Scene Parsing +3

Revamp: Enhancing Accessible Information Seeking Experience of Online Shopping for Blind or Low Vision Users

no code implementations1 Feb 2021 Ruolin Wang, Zixuan Chen, Mingrui "Ray" Zhang, Zhaoheng Li, Zhixiu Liu, Zihan Dang, Chun Yu, Xiang "Anthony" Chen

Online shopping has become a valuable modern convenience, but blind or low vision (BLV) users still face significant challenges using it, because of: 1) inadequate image descriptions and 2) the inability to filter large amounts of information using screen readers.

Descriptive Information Retrieval +2

Thinking in Frequency: Face Forgery Detection by Mining Frequency-aware Clues

2 code implementations ECCV 2020 Yuyang Qian, Guojun Yin, Lu Sheng, Zixuan Chen, Jing Shao

As realistic facial manipulation technologies have achieved remarkable progress, social concerns about potential malicious abuse of these technologies bring out an emerging research topic of face forgery detection.

You Impress Me: Dialogue Generation via Mutual Persona Perception

1 code implementation ACL 2020 Qian Liu, Yihong Chen, Bei Chen, Jian-Guang Lou, Zixuan Chen, Bin Zhou, Dongmei Zhang

Despite the continuing efforts to improve the engagingness and consistency of chit-chat dialogue systems, the majority of current work simply focus on mimicking human-like responses, leaving understudied the aspects of modeling understanding between interlocutors.

Ranked #2 on Dialogue Generation on Persona-Chat (using extra training data)

Dialogue Generation

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