Search Results for author: Jingen Liu

Found 22 papers, 4 papers with code

Text-guided Eyeglasses Manipulation with Spatial Constraints

no code implementations25 Apr 2023 Jiacheng Wang, Ping Liu, Jingen Liu, Wei Xu

To address these limitations, we propose a Text-guided Eyeglasses Manipulation method that allows for control of the eyeglasses shape and style based on a binary mask and text, respectively.

Virtual Try-on

Video2StyleGAN: Encoding Video in Latent Space for Manipulation

no code implementations27 Jun 2022 Jiyang Yu, Jingen Liu, Jing Huang, Wei zhang, Tao Mei

To this end, we propose a novel network to encode face videos into the latent space of StyleGAN for semantic face video manipulation.

A-ACT: Action Anticipation through Cycle Transformations

no code implementations2 Apr 2022 Akash Gupta, Jingen Liu, Liefeng Bo, Amit K. Roy-Chowdhury, Tao Mei

To incorporate this ability in intelligent systems a question worth pondering upon is how exactly do we anticipate?

Action Anticipation

Cross-modal Contrastive Distillation for Instructional Activity Anticipation

no code implementations18 Jan 2022 Zhengyuan Yang, Jingen Liu, Jing Huang, Xiaodong He, Tao Mei, Chenliang Xu, Jiebo Luo

In this study, we aim to predict the plausible future action steps given an observation of the past and study the task of instructional activity anticipation.

Knowledge Distillation

Smart Director: An Event-Driven Directing System for Live Broadcasting

no code implementations11 Jan 2022 Yingwei Pan, Yue Chen, Qian Bao, Ning Zhang, Ting Yao, Jingen Liu, Tao Mei

To our best knowledge, our system is the first end-to-end automated directing system for multi-camera sports broadcasting, completely driven by the semantic understanding of sports events.

Event Detection Highlight Detection

Automated Pulmonary Embolism Detection from CTPA Images Using an End-to-End Convolutional Neural Network

no code implementations10 Nov 2021 Yi Lin, Jianchao Su, Xiang Wang, Xiang Li, Jingen Liu, Kwang-Ting Cheng, Xin Yang

We have evaluated our approach using the 20 CTPA test dataset from the PE challenge, achieving a sensitivity of 78. 9%, 80. 7% and 80. 7% at 2 false positives per volume at 0mm, 2mm and 5mm localization error, which is superior to the state-of-the-art methods.

Pulmonary Embolism Detection

Trustworthy AI: From Principles to Practices

no code implementations4 Oct 2021 Bo Li, Peng Qi, Bo Liu, Shuai Di, Jingen Liu, JiQuan Pei, JinFeng Yi, BoWen Zhou

In this review, we provide AI practitioners with a comprehensive guide for building trustworthy AI systems.

Fairness

CoSeg: Cognitively Inspired Unsupervised Generic Event Segmentation

1 code implementation30 Sep 2021 Xiao Wang, Jingen Liu, Tao Mei, Jiebo Luo

Unlike the mainstream clustering-based methods, our framework exploits a transformer-based feature reconstruction scheme to detect event boundary by reconstruction errors.

Boundary Detection Event Segmentation +1

Memory-Augmented Non-Local Attention for Video Super-Resolution

1 code implementation CVPR 2022 Jiyang Yu, Jingen Liu, Liefeng Bo, Tao Mei

Those methods achieve limited performance as they suffer from the challenge in spatial frame alignment and the lack of useful information from similar LR neighbor frames.

Analog Video Restoration Video Super-Resolution

Automated Deepfake Detection

no code implementations20 Jun 2021 Ping Liu, Yuewei Lin, Yang He, Yunchao Wei, Liangli Zhen, Joey Tianyi Zhou, Rick Siow Mong Goh, Jingen Liu

In this paper, we propose to utilize Automated Machine Learning to adaptively search a neural architecture for deepfake detection.

BIG-bench Machine Learning DeepFake Detection +1

Toward Accurate and Realistic Outfits Visualization with Attention to Details

no code implementations CVPR 2021 Kedan Li, Min Jin Chong, Jeffrey Zhang, Jingen Liu

Prior works produce images that are filled with artifacts and fail to capture important visual details necessary for commercial applications.

Image Generation Virtual Try-on

Action Unit Memory Network for Weakly Supervised Temporal Action Localization

no code implementations CVPR 2021 Wang Luo, Tianzhu Zhang, Wenfei Yang, Jingen Liu, Tao Mei, Feng Wu, Yongdong Zhang

In this paper, we present an Action Unit Memory Network (AUMN) for weakly supervised temporal action localization, which can mitigate the above two challenges by learning an action unit memory bank.

Weakly Supervised Action Localization Weakly-supervised Temporal Action Localization +1

Learning a Unified Sample Weighting Network for Object Detection

1 code implementation CVPR 2020 Qi Cai, Yingwei Pan, Yu Wang, Jingen Liu, Ting Yao, Tao Mei

To this end, we devise a general loss function to cover most region-based object detectors with various sampling strategies, and then based on it we propose a unified sample weighting network to predict a sample's task weights.

General Classification Object +3

Robust Visual Object Tracking with Two-Stream Residual Convolutional Networks

no code implementations13 May 2020 Ning Zhang, Jingen Liu, Ke Wang, Dan Zeng, Tao Mei

Inspired by the human "visual tracking" capability which leverages motion cues to distinguish the target from the background, we propose a Two-Stream Residual Convolutional Network (TS-RCN) for visual tracking, which successfully exploits both appearance and motion features for model update.

Visual Object Tracking Visual Tracking +1

Toward Accurate and Realistic Virtual Try-on Through Shape Matching and Multiple Warps

no code implementations22 Mar 2020 Kedan Li, Min Jin Chong, Jingen Liu, David Forsyth

However, obtaining a realistic image is challenging because the kinematics of garments is complex and because outline, texture, and shading cues in the image reveal errors to human viewers.

Image Generation Virtual Try-on

Theme-Matters: Fashion Compatibility Learning via Theme Attention

no code implementations12 Dec 2019 Jui-Hsin Lai, Bo Wu, Xin Wang, Dan Zeng, Tao Mei, Jingen Liu

This model associates themes with the pairwise compatibility with attention, and thus compute the outfit-wise compatibility.

Fashion Compatibility Learning

Self-Supervised Spatiotemporal Feature Learning via Video Rotation Prediction

no code implementations28 Nov 2018 Longlong Jing, Xiaodong Yang, Jingen Liu, YingLi Tian

The success of deep neural networks generally requires a vast amount of training data to be labeled, which is expensive and unfeasible in scale, especially for video collections.

Self-Supervised Action Recognition Temporal Action Localization +1

Zero-Shot Event Detection by Multimodal Distributional Semantic Embedding of Videos

no code implementations2 Dec 2015 Mohamed Elhoseiny, Jingen Liu, Hui Cheng, Harpreet Sawhney, Ahmed Elgammal

To our knowledge, this is the first Zero-Shot event detection model that is built on top of distributional semantics and extends it in the following directions: (a) semantic embedding of multimodal information in videos (with focus on the visual modalities), (b) automatically determining relevance of concepts/attributes to a free text query, which could be useful for other applications, and (c) retrieving videos by free text event query (e. g., "changing a vehicle tire") based on their content.

Event Detection

Pedestrian Detection in Low-resolution Imagery by Learning Multi-scale Intrinsic Motion Structures (MIMS)

no code implementations CVPR 2014 Jiejie Zhu, Omar Javed, Jingen Liu, Qian Yu, Hui Cheng, Harpreet Sawhney

In this paper, we give a comparative evaluation of the proposed method and demonstrate that MIMS outperforms the state of the art approaches in identifying pedestrians from low resolution airborne videos.

Optical Flow Estimation Pedestrian Detection

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