Search Results for author: Zhe Wu

Found 22 papers, 8 papers with code

Weakly-Supervised Crowd Counting Learns from Sorting rather than Locations

no code implementations ECCV 2020 Yifan Yang, Guorong Li, Zhe Wu, Li Su, Qingming Huang, Nicu Sebe

We propose a soft-label sorting network along with the counting network, which sorts the given images by their crowd numbers.

Crowd Counting

Lightweight Delivery Detection on Doorbell Cameras

no code implementations13 May 2023 Pirazh Khorramshahi, Zhe Wu, Tianchen Wang, Luke DeLuccia, Hongcheng Wang

Despite recent advances in video-based action recognition and robust spatio-temporal modeling, most of the proposed approaches rely on the abundance of computational resources to afford running huge and computation-intensive convolutional or transformer-based neural networks to obtain satisfactory results.

Action Recognition

Learning Spatial-Frequency Transformer for Visual Object Tracking

2 code implementations18 Aug 2022 Chuanming Tang, Xiao Wang, Yuanchao Bai, Zhe Wu, Jianlin Zhang, YongMei Huang

To handle these issues, in this paper, we propose a unified Spatial-Frequency Transformer that models the Gaussian spatial Prior and High-frequency emphasis Attention (GPHA) simultaneously.

Visual Object Tracking

ORDSIM: Ordinal Regression for E-Commerce Query Similarity Prediction

no code implementations13 Mar 2022 Md. Ahsanul Kabir, Mohammad Al Hasan, Aritra Mandal, Daniel Tunkelang, Zhe Wu

ORDSIM exploits variable-width buckets to model ordinal loss, which penalizes errors in high-level similarity harshly, and thus enable the regression model to obtain better prediction results for high similarity values.


Full-Duplex Strategy for Video Object Segmentation

1 code implementation ICCV 2021 Ge-Peng Ji, Deng-Ping Fan, Keren Fu, Zhe Wu, Jianbing Shen, Ling Shao

Previous video object segmentation approaches mainly focus on using simplex solutions between appearance and motion, limiting feature collaboration efficiency among and across these two cues.

Salient Object Detection Semantic Segmentation +4

L2E: Learning to Exploit Your Opponent

no code implementations18 Feb 2021 Zhe Wu, Kai Li, Enmin Zhao, Hang Xu, Meng Zhang, Haobo Fu, Bo An, Junliang Xing

In this work, we propose a novel Learning to Exploit (L2E) framework for implicit opponent modeling.

OpenHoldem: A Benchmark for Large-Scale Imperfect-Information Game Research

no code implementations11 Dec 2020 Kai Li, Hang Xu, Enmin Zhao, Zhe Wu, Junliang Xing

Owning to the unremitting efforts by a few institutes, significant progress has recently been made in designing superhuman AIs in No-limit Texas Hold'em (NLTH), the primary testbed for large-scale imperfect-information game research.

Label Decoupling Framework for Salient Object Detection

1 code implementation CVPR 2020 Jun Wei, Shuhui Wang, Zhe Wu, Chi Su, Qingming Huang, Qi Tian

Though remarkable progress has been achieved, we observe that the closer the pixel is to the edge, the more difficult it is to be predicted, because edge pixels have a very imbalance distribution.

object-detection RGB Salient Object Detection +2

VideoSSL: Semi-Supervised Learning for Video Classification

no code implementations29 Feb 2020 Longlong Jing, Toufiq Parag, Zhe Wu, YingLi Tian, Hongcheng Wang

To minimize the dependence on a large annotated dataset, our proposed semi-supervised method trains from a small number of labeled examples and exploits two regulatory signals from unlabeled data.

Classification General Classification +1

Multi-View Photometric Stereo: A Robust Solution and Benchmark Dataset for Spatially Varying Isotropic Materials

no code implementations18 Jan 2020 Min Li, Zhenglong Zhou, Zhe Wu, Boxin Shi, Changyu Diao, Ping Tan

From a single viewpoint, we use a set of photometric stereo images to identify surface points with the same distance to the camera.

Recognizing Instagram Filtered Images with Feature De-stylization

1 code implementation30 Dec 2019 Zhe Wu, Zuxuan Wu, Bharat Singh, Larry S. Davis

Deep neural networks have been shown to suffer from poor generalization when small perturbations are added (like Gaussian noise), yet little work has been done to evaluate their robustness to more natural image transformations like photo filters.

Style Transfer

Stacked Cross Refinement Network for Edge-Aware Salient Object Detection

1 code implementation ICCV 2019 Zhe Wu, Li Su, Qingming Huang

Motivated by the logical interrelations between binary segmentation and edge maps, we propose a novel Stacked Cross Refinement Network (SCRN) for salient object detection in this paper.

Edge Detection object-detection +2

Automatic Long-Term Deception Detection in Group Interaction Videos

no code implementations15 May 2019 Chongyang Bai, Maksim Bolonkin, Judee Burgoon, Chao Chen, Norah Dunbar, Bharat Singh, V. S. Subrahmanian, Zhe Wu

Most work on automated deception detection (ADD) in video has two restrictions: (i) it focuses on a video of one person, and (ii) it focuses on a single act of deception in a one or two minute video.

Deception Detection

Soft Sampling for Robust Object Detection

1 code implementation18 Jun 2018 Zhe Wu, Navaneeth Bodla, Bharat Singh, Mahyar Najibi, Rama Chellappa, Larry S. Davis

Interestingly, we observe that after dropping 30% of the annotations (and labeling them as background), the performance of CNN-based object detectors like Faster-RCNN only drops by 5% on the PASCAL VOC dataset.

object-detection Robust Object Detection

Deception Detection in Videos

no code implementations12 Dec 2017 Zhe Wu, Bharat Singh, Larry S. Davis, V. S. Subrahmanian

We present a system for covert automated deception detection in real-life courtroom trial videos.

Action Recognition Deception Detection In Videos +1

VITON: An Image-based Virtual Try-on Network

6 code implementations CVPR 2018 Xintong Han, Zuxuan Wu, Zhe Wu, Ruichi Yu, Larry S. Davis

We present an image-based VIirtual Try-On Network (VITON) without using 3D information in any form, which seamlessly transfers a desired clothing item onto the corresponding region of a person using a coarse-to-fine strategy.

Virtual Try-on

A Benchmark Dataset and Evaluation for Non-Lambertian and Uncalibrated Photometric Stereo

no code implementations CVPR 2016 Boxin Shi, Zhe Wu, Zhipeng Mo, Dinglong Duan, Sai-Kit Yeung, Ping Tan

Recent progress on photometric stereo extends the technique to deal with general materials and unknown illumination conditions.

Towards Building an RGBD-M Scanner

no code implementations12 Mar 2016 Zhe Wu, Sai-Kit Yeung, Ping Tan

We present a portable device to capture both shape and reflectance of an indoor scene.

Selecting Relevant Web Trained Concepts for Automated Event Retrieval

no code implementations ICCV 2015 Bharat Singh, Xintong Han, Zhe Wu, Vlad I. Morariu, Larry S. Davis

Given a text description of an event, event retrieval is performed by selecting concepts linguistically related to the event description and fusing the concept responses on unseen videos.

Domain Adaptation Retrieval

Multi-view Photometric Stereo with Spatially Varying Isotropic Materials

no code implementations CVPR 2013 Zhenglong Zhou, Zhe Wu, Ping Tan

We present a method to capture both 3D shape and spatially varying reflectance with a multi-view photometric stereo technique that works for general isotropic materials.

Calibrating Photometric Stereo by Holistic Reflectance Symmetry Analysis

no code implementations CVPR 2013 Zhe Wu, Ping Tan

Under unknown directional lighting, the uncalibrated Lambertian photometric stereo algorithm recovers the shape of a smooth surface up to the generalized bas-relief (GBR) ambiguity.

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