Program
We encourage paper submissions and welcome you to attend AVSS 2019. Please see Call for Papers for details.
Program Overview:
- Main Coferene: 2.5 days
- Workshops/Challenges and Tutorials: 1 day
9/18 Wed | 9/19 Thr | 9/20 Fri | 9/21 Sat | |
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Morning | Keynote I | Keynote III | Keynote V | Workshops Tutorials |
Oral Session I | Oral Session III | Oral Session V | ||
Poster Session I | Poster Session III | Poster Session V | ||
Lunch | ||||
Afternoon | Keynote II | Keynote IV | City Tour | Workshops Tutorials |
Oral Session II | Oral Session IV | |||
Panel I | Panel IV | |||
Poster Session II | Oral Session IV | |||
Dinner | Reception | Banquet | Adjoint |
Note that ICIP 2019 Taipei is a back-to-back conference on 9/22 (Sun) to 9/25 (Wed).
Program Schedule
All Conference and Workshop meeting rooms are in the Gong-Cheng Building (公誠樓) of University of Taipei (UTaipei) - Bo-Ai Campus (臺北市立大學博愛校區). See map in the Venue page.
Main Conference Day 1 (9/18 Wednesday) at Conference Room 3 (會議室三)
8:20 to 8:40 Opening Ceremony
8:40 to 9:40 Keynote I - Prof. Mubarak Shah
9:40 to 10:00 Coffee Break
10:00 to 11:00 Oral I (3 papers, session chair: Prof. Mubarak Shah)
11:00 to 12:00 Poster I (8+3 posters)
12:00 to 1:30 Lunch
1:30 to 2:30 Keynote II - Prof. Jenq-Neng Hwang
2:30 to 3:30 Oral II (3 papers, session chair: Prof. Jenq-Neng Hwang)
3:30 to 3:50 Coffee Break
3:50 to 4:30 Panel Discussion I (Industrial Perspectives on the 3rd wave of AI)
4:30 to 5:30 Poster II (8+3 posters)
5:30 to 8:00 Reception at the Venue
Main Conference Day 2 (9/19 Thursday) at Conference Room 3 (會議室三)
8:20 to 8:40 Opening (Announcements)
8:40 to 9:40 Keynote III - Dr. Jeff Alstott
9:40 to 10:00 Coffee Break
10:00 to 11:00 Oral III (3 papers, chair: Dr. Jeff Alstott)
11:00 to 12:00 Poster III (8+3 posters)
12:00 to 1:30 Lunch
1:30 to 2:30 Keynote IV - Dr. Hong-Yuan Mark Liao
2:30 to 3:30 Oral IV (3 papers, session chair: Dr. Hong-Yuan Mark Liao)
3:30 to 3:50 Coffee Break
3:50 to 4:30 Panel Discussion II (Ethics & Forensics of AI)
4:30 to 5:30 Poster IV (8+3 posters)
5:30 to 7:30 Coffee Break and transport to Banquet Restaurant
7:30 to 10:30 Banquet
Main Conference Day 3 (9/20 Friday) at Conference Room 3 (會議室三)
8:20 to 8:40 Opening (Announcements)
8:40 to 9:40 Keynote V - Prof. Rama Chellappa
9:40 to 10:00 Coffee Break
10:00 to 11:00 Oral V (3 papers, session chair: Prof. Rama Chellappa)
11:00 to 12:00 Poster V (8+3 posters)
12:00 to 5:00 City Tour
Please sign up during Registration or in the conference no later than the Banquet night, so we can better control head counts for the organization of these tours. We encourage you to bring friends and family members to join the half-day trip. Note that we will provide student volunteering tour guides, but all the expense of the tour (transportation, food, ticket) is is out of your own pocket.
- City Tour Group 1: Taipei 101 & Xiangshan Trail
- City Tour Group 2: National Palace Museum & Thermal Valley
- City Tour Group 3: Taipei Zoo & Maokong Crystal Gondola (good for family with young kids)
Workshops and Tutorials (9/21 Saturday)
Refer to Workshops and Tutorials for details. Note that each workshop might have difference start and end time, please refer to each workshop website for details. We maintain the same Coffee Break and Lunch time as the main conference across all workshops and tutorials:
9:40 to 10:00 Coffee Break
12:00 to 1:30 Lunch
3:30 to 3:50 Coffee Break
Tutorial I: Automatic Detection of Abnormal Events in Surveillance Videos fro Online Processing and Low-cost Devices
- Speaker: Victor Sanchez, University of Warwick, UK.
- Time: 9/21 Sat 8:00am to 12:00pm
- Room: Conference Room 1 (會議室一)
Tutorial II: Deep Learning for Video Compression and Understanding
- Speaker: Wanli Quyang, University of Sydney
- Time: 9/21 Sat 8:00am to 12:00pm
- Room: Conference Room 1 (會議室二)
Workshop (morning): Biometrics for Smart Cities.
- Time: 9/21 Sat 8:00am to 12:00pm
- Room: Classroom 1 (教室一)
Workshop (morning): The 3th International Workshop on Traffic and Street Surveillance for Safety and Security (IWT4S)
- Time: 9/21 Sat 8:00am to 12:00pm
- Room: Classroom 2 (教室二)
Workshop (morning): The 2nd International Workshop on Small-Drone Surveillance, Detection and Counteraction Techniques (WOSDETC)
- Time: 9/21 Sat 8:00am to 12:00pm
- Room: Computer Room 1 (電腦教室一)
Workshop (afternoon): The Content-Aware Video Analysis (CAVA)Workshop
- Time: 9/21 Sat 1:30pm to 5:30pm
- Room: Classroom 1 (教室一)
Workshop (afternoon): Visual Computing for Computer Vision and Intelligent Transportation System (VCAVSS)
- Time: 9/21 Sat 1:30pm to 5:30pm
- Room: Classroom 2 (教室二)
Workshop (afternoon): The Deep Learning in Activity Monitoring (DLAM) Workshop
- Time: 9/21 Sat 1:30pm to 5:30pm
- Room: Computer Room 1 (電腦教室一)
Panel Discussions
Panel Discussion I: Industrial Perspectives on the 3rd wave of AI
Or actually the discussion is more about Philosophy vs. the 3rd Wave of AI. Refer to Peter Tu's inspirational slides at 2019_AVSS_Third_Wave_AI _Panel_Discussion.pdf.
9/18 Wednesday 3:50 to 4:30pm at Conference Room 3 (會議室三)
- Panel Chair: Dr. Peter Tu (GE Global Research)
Artificial Intelligence has been characterized in terms of waves. During the first wave we explored the idea of logical reasoning. Success in the second wave is primarily based on statistical inference. Those that are calling for the third wave of AI argue for systems that when confronted by unforeseen circumstances can reason over contextual cues and then do the right thing. The questions that we will consider during this panel discussion will revolve around Industries response to the third wave of AI. Topics of discussion may include: the grounding problem, associative and episodic memory, narratives, causality, analogies and questions regarding intentionality.
Panelists (including but not limited to):
- Rama Chellappa (University of Maryland, College Park, USA)
- Jenq-Neng Hwang (University of Washington, USA)
Panel Discussion II: Ethics & Forensics of AI
See kick off slides at AVSS10_Panel2_Ethics_Forensics.pdf.
9/19 Thursday 3:50 to 4:30pm at Conference Room 3 (會議室三)
- Panel Chair: Prof. Siwei Lyu, Prof. Ming-Ching Chang (University at Albany - SUNY)
The development of AI technology, in particularly, deep learning and their applications in computer vision, has brought forth significant advances to surveillance. With the improvement in performance, they also introduce new challenges to the research community. In particular, there are three areas that are of important concerns:
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biases: the heavy reliance of the deep learning based systems on annotated training data also introduce biases to under-represented social groups in the trained system, thus their fairness with regards to established social values is an important concern recently.
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malicious attacks: deep learning based systems are fragile and susceptible to malicious attacks in the form of training data poisoning, deep network backdoor or adversarial examples. As such the security of the deep learning based surveillance systems needs to be addressed.
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manipulations: deep learning based methods can also be used to create or tamper digital audiovisual signals (e.g., DeepFakes) misleading surveillance systems and we need to develop effective forensic technology to counter the fake media.
Furthermore, the increasing scales of automatic video surveillance, especially face recognition has also raised significant concerns about the ethical issues in using such technologies. The technical community should also pay attention to the general responsibility to the society.
This panel will provide the audience a comprehensive overview of these issues and focus on an in-depth discussion about their impact to future research directions.
Panelists (including but not limited to):
- James Ferryman (University of Reading, UK)
- Guangliang Zhao (GE Research, USA)
- Gee-Sern Jison Hsu (National Taiwan University of Science and Technology)
Full Program and Presentation Schedule
Note that all oral papers will also present their posters in their respective session.
Day 1 (9/18 Wed.) Session I (Oral I + Poster I)
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Paper ID 12 - Person Head Detection Based Deep Model for People Counting in Sports Videos
Sultan Daud Khan (University of Ha'il); Habib Ullah (University of Ha'il); Mohib Ullah (NTNU)*; Nicola Conci (UNITN); Faouzi Alaya-Chekh (NTNU at Gjvik, Norway); Azeddine Beghdadi (L2TI, University Paris 13) -
Paper ID 69 - Improving Person Re-identification by Combining Siamese Convolutional Neural Network and Re-ranking Process
Nabila Mansouri (ReDCAD)*; Sourour Ammar (MIRACL Laboratory); Yousri Kessentini (MIRACL Laboratory)
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Paper ID 100 - An interactive Framework for Cross-modal Attribute-based Person Retrieval
Andreas Specker (Fraunhofer IOSB)*; Arne Schumann (Fraunhofer IOSB); Jürgen Beyerer (Fraunhofer IOSB)
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Paper ID 99 - Suggesting Gaze-based Selection for Surveillance Applications
Jutta Hild (Fraunhofer IOSB)*; Elisabeth Peinsipp-Byma (Fraunhofer IOSB); Michael Voit (Fraunhofer IOSB); Jürgen Beyerer (Fraunhofer IOSB)
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Paper ID 32 - Pedestrian Parsing by Joint Learning from Wholes and Parts
Zhenting Gong (Beijing Sogou Technology Development Co., Ltd.); Yang Yang (Chinese Academy of Sciences)* -
Paper ID 51 - Real-time Video-based Person Re-identification Surveillance with Light-weight Deep Convolutional Networks
Chien-Yao Wang (Institute of Information Science, Academia Sinica)*; Ping-Yang Chen (National Taiwan Ocean University); Ming-Chiao Chen (National Taitung University); Jun-Wei Hsieh (National Taiwan Ocean University); Mark Liao (Institute of Information Science, Academia Sinica) -
Paper ID 38 - DYNAMIC GALLERY FOR REAL-TIME MULTI-TARGET MULTI-CAMERA TRACKING
Yu-Sheng Chou (National Taiwan University)*; Chien-Yao Wang (Institute of Information Science, Academia Sinica); Ming-Chiao Chen (National Taitung University); Shou-De Lin (NTU); Mark Liao (Institute of Information Science, Academia Sinica)
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Paper ID 112 - UHCTD: A Comprehensive Dataset for Camera Tampering Detection
Pranav Mantini (University of Houston)*; Shishir Shah (University of Houston)
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Paper ID 19 - 3DMA: A Multi-modality 3D Mask Face Anti-spoofing Database
Jinchuan Xiao (National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences)*; Yang Yang (Chinese Academy of Sciences); Jianzhu Guo (NLPR); Yinhang Tang (AuthenMetric Inc.); Zhen Lei (NLPR, CASIA, China)
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Paper ID 7 - A Camera Recalibration Method for a Top-view Surveillance System Based on Relative Camera Pose and Structural Similarity
Jun Minagawa (Mitsubishi Electric Corporation)*; Kohei Okahara (Mitsubishi Electric Corporation); Kento Yamazaki (Mitsubishi Electric Corporation); Tsukasa Fukasawa ( Mitsubishi Electric Corporation)
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Paper ID 61 - CNN-Based Analysis of Crowd Structure using Automatically Annotated Training Data
M. Sami Zitouni (Khalifa University)*; ANDRZEJ SLUZEK (Khalifa University); Harish Bhaskar (Khalifa University)
Oral I (10:00 to 11:00)
Poster I (11:00 to 12:00)
Day 1 (9/18 Wed.) Session II (Oral II + Poster II)
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Paper ID 96 - RGB-Depth Cross-Modal Person Re-identification
Frank Michael Hafner (ZF Friedrichshafen AG)*; Amran Bhuiyan (École de technologie supérieure); Julian F P Kooij (Delft University of Technology); Eric Granger (ETS Montreal)
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Paper ID 17 - Continuous Learning without Forgetting for Person Re-Identification Task
Nehemia Sugianto (Southern Cross University)*; Dian Tjondronegoro (Griffith University); Golam Sorwar (Southern Cross University); Prithwi Chakraborty (Southern Cross University); Elizabeth Irenne Yuwono (Southern Cross University)
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Paper ID 36 - Video-based Person Re-identification Using Refined Attention Networks
Tanzila Rahman (University of Manitoba)*; Mrigank Rochan (University of Manitoba); Yang Wang (University of Manitoba)
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Paper ID 8 - Non-local Attentive Temporal Network for Video-based Person Re-Identification
Shivansh Rao (Delhi Technological University); Peng Cao (University of Electronic Science and Technology of China); Tanzila Rahman (University of British Columbia); Mrigank Rochan (University of Manitoba); Yang Wang (University of Manitoba)*
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Paper ID 72 - What Makes You Look Like You: Learning an Inherent Feature Representation for Person Re-Identification
Wen-Li Wei (Academia Sinica); Jen-Chun Lin (Yuan Ze University)*; Yen-Yu Lin (Academia Sinica); Mark Liao (Institute of Information Science, Academia Sinica)
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Paper ID 79 - A Comprehensive Study on Large-Scale Person Retrieval in Real Surveillance Scenarios
Da Li (University of Chinese Academy of Sciences)*; Zhang Zhang (Institute of Automation, Chinese Academy of Sciences); Caifeng Shan (CAS-AIR); Liang Wang (NLPR, China); Tieniu Tan (NLPR, China)
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Paper ID 56 - Gaussian Normalization: Handling Burstiness in Visual Data
remi trichet (DCU)*; Noel O'Connor (DCU) -
Paper ID 68 - Fast tracking-by-detection of bus passengers with Siamese CNNs
Claire Labit-Bonis (LAAS-CNRS / ACTIA Automotive)*; Frederic Lerasle (LAAS-CNRS); Francisco Madrigal (LAAS); Jérôme Thomas (Actia Automotive)
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Paper ID 75 - On the Interaction Between Deep Detectors and Siamese Trackers in Video Surveillance
Madhu Kiran (LIVIA)*; Vivek Tiwari (Indian Institute of Technology (ISM), Dhanbad); Le Thanh NGUYEN-MEIDINE (LIVIA); Louis-Antoine Blais-Morin (Genetec Inc.); Eric Granger (ETS Montreal)
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Paper ID 103 - Simple background subtraction constraint for weakly supervised background subtraction network
Tsubasa Minematsu (Kyushu university)*; Atsushi Shimada (Kyushu University); RIN-ICHIRO TANIGUCHI (Kyushu University, Japan)
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Paper ID 85 - Enhancing object detection in the dark using U-Net based restoration module
Yen-Ting Huang (National Chengchi University)*; Yan-Tsung Peng (National Chengchi University); Wen-Hung Liao (National Chengchi University)
Oral II (2:30 to 3:30)
Poster II (4:30 to 5:30)
Day 2 (9/19 Thr.) Session III (Oral III + Poster III)
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Paper ID 14 - Self-Attention Temporal Convolutional Network for Long-Term Daily Living Activity Detection
Rui Dai (INRIA)*; Luca Minciullo (Toyota-Europe); Lorenzo Garattoni (Toyota-Europe); Gianpiero Francesca (Toyota-Europe); Francois Bremond (Inria Sophia Antipolis, France)
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Paper ID 107 - Information theory based pruning for CNN compression and its application to image classification and action recognition
Hai-Hong Phan (ETIS/Université Paris Seine, Université Cergy-Pontoise, ENSEA, CNRS/ 95000-Cergy)*; Ngoc-Son Vu (ETIS/Université Paris Seine, Université Cergy-Pontoise, ENSEA, CNRS/ 95000-Cergy)
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Paper ID 21 - Efficient Violence Detection Using 3D Convolutional Neural Networks
Ji Li (Shanghai Jiao Tong University); Xinghao Jiang (Shanghai Jiao Tong University)*; Tanfeng Sun (Shanghai Jiao Tong University); Ke Xu (Shanghai Jiao Tong University) -
Paper ID 18 - Future Frame Prediction Using Convolutional VRNN for Anomaly Detection
Yiwei Lu (University of Manitoba)*; Mahesh Kumar K (University of Manitoba); Seyed shahabeddin Nabavi (University of Manitoba); Yang Wang (University of Manitoba)
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Paper ID 67 - A new Bayesian modeling for 3D human-object action recognition
Camille Maurice (LAAS-CNRS)*; Francisco Madrigal (LAAS); Frederic Lerasle (LAAS-CNRS) -
Paper ID 71 - An Exploration on Temperature Term in Training Deep Neural Network
Zhaofeng Si (University of Chinese Academy of Sciences)*; Honggang Qi (University of Chinese Academy of Sciences)
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Paper ID 86 - Pose Guided Dynamic Image Network for Human Action Recognition in Person Centric Videos
Sachin Chaudhary (IIT Ropar)*; Akshay A Dudhane (IIT Ropar); Subrahmanyam Murala (IIT Ropar)
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Paper ID 89 - SkeleMotion: A New Representation of Skeleton Joint Sequences Based on Motion Information for 3D Action Recognition
Carlos A Caetano (Universidade Federal de Minas Gerais - UFMG)*; Jessica Sena de Souza (Federal University of Minas Gerais); Francois Bremond (Inria Sophia Antipolis, France); Jefersson A dos Santos (UFMG); William R Schwartz (Federal University of Minas Gerais)
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Paper ID 106 - Supervised People Counting Using An Overhead Fisheye Camera
Shengye Li (Boston University); Ozan Tezcan (Boston University)*; Janusz Konrad (Boston University, Massachusetts); Prakash Ishwar (Boston University) -
Paper ID 128 - Automated Real-time Anomaly Detection in Human Trajectories using Sequence to Sequence Networks
Giorgos Bouritsas (National Center for Scientific Research and currently with the Imperial College London)*; Stelios Daveas (National Center for Scientific Research "Demokritos"); Antonios Danelakis (National Center for Scientific Research "Demokritos"); Constantinos Rizogiannis (National Center for Scientific Research "Demokritos"); Stelios Thomopoulos (National Center for Scientific Research "Demokritos")
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Paper ID 130 - Social MIL: Interaction-Aware for Crowd Anomaly Detection
Shuheng Lin (Shanghai Jiao Tong University); Hua Yang (Shanghai Jiao Tong University)*; Lin Chen (Shanghai Jiao Tong University); Tianqi Shi (Shanghai Jiao Tong University)
Oral III (10:00 to 11:00)
Poster III (11:00 to 12:00)
Day 2 (9/19 Thr.) Session IV (Oral IV + Poster IV)
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Paper ID 26 - Crowd Behaviour Characterization for Scene Tracking
Gianni Franchi (Paris-Sud University)*; Emanuel Aldea (University Paris Sud); Severine Dubuisson (Aix-Marseille University); Isabelle Bloch (LTCI, Télécom ParisTech, Université Paris-Saclay, Paris, France)
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Paper ID 25 - OptInOpt: Dual Optimization for Automatic Camera Calibration by Multi-Target Observations
Vojtěch Bartl (FIT BUT)*; Adam Herout (FIT BUT) -
Paper ID 64 - Deep Face Image Retrieval for Cancelable Biometric Authentication
Young Kyun Jang (Seoul National University)*; Nam Ik Cho (Seoul National University)
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Paper ID 81 - Image and Video Super Resolution using Recurrent Generative Adversarial Network
Omkar Thawakar (SGGSIE&T)*; Prashant Patil (IIT Ropar); Akshay A Dudhane (IIT Ropar); Subrahmanyam Murala (IIT Ropar); Uday Kulkarni (SGGSIET, Nanded)
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Paper ID 98 - Constraining Relative Camera Pose Estimation with Pedestrian Detector-Based Correspondence Filters
Emanuel Aldea (University Paris Sud)*; Thomas Pollok (Fraunhofer IOSB); Chengchao Qu (Fraunhofer IOSB) -
Paper ID 125 - A Learning Approach to Interactive Advertising
Peter Tu (General Electric)*; James Kubricht (General Electric); Alberto Santamaria Pang (General Electric); Tao Gao (UCLA); Alex Chen (General Electric); Don Hamilton (General Electric); Justin Foehner (General Electric) -
Paper ID 101 - INCREMENTAL LEARNING OF ABNORMALITIES IN AUTONOMOUS SYSTEMS
Hassan Zaal (Genoa University and Queen Mary University of London)*; hafsa iqbal (university of genoa); Damian A Campo (Genova University); LUCIO MARCENARO (Universita degli Studi di Genoa, Genoa); Carlo Regazzoni (Universita degli Studi di Genoa, Genoa)
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Paper ID 73 - ABNORMALITY DETECTION USING GRAPH MATCHING FOR MULTI-TASK DYNAMICS OF AUTONOMOUS SYSTEMS
Hassan Zaal (Genoa University and Queen Mary University of London)*; Mohamad Baydoun (Unviersity of Genova); LUCIO MARCENARO (Universita degli Studi di Genoa, Genoa); Laurissa Tokarchuk (Queen Mary University of London); Carlo Regazzoni (Universita degli Studi di Genoa, Genoa)
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Paper ID 41 - Vein Pattern Visualisation and Feature Extraction Using Sparse Auto-encoder for Forensic Purposes
Soheil Varastehpour (Unitec Institute of Technology)*; Hamid Sharifzadeh (Unitec Institute of Technology); Iman Tabatabaei Ardekani (Unitec Institute of Technology); Xavier Francis (Unitec Institute of Technology) -
Paper ID 62 - K-Same-Siamese-GAN: k-Same Algorithm with Generative Adversarial Network for Facial Image De-identification with Hyperparameter Tuning and Mixed Precision Training
Yi-Lun Pan (National Taiwan University)*; Min-Jhih Haung (National Taiwan University); Kuo-Teng Ding (National Taiwan University); Ja-Ling Wu (National Taiwan University); Roger Jang
Oral IV (2:30 to 3:30)
Poster IV (4:30 to 5:30)
Day 3 (9/20 Fri.) Session V (Oral V + Poster V)
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Paper ID 47 - Spatial Attention for Pedestrian Detection
Ujjwal Ujjwal (INRIA)*; Aziz Dziri (VEDECOM); Bertrand Leroy (VEDECOM); Francois Bremond (Inria Sophia Antipolis, France)
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Paper ID 46 - Inverse Attention Guided Deep Crowd Counting
Vishwanath Sindagi (Johns Hopkins University)*; Vishal Patel (Johns Hopkins University)
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Paper ID 48 - Graph-to-Graph Energy Minimization for Video Object Segmentation
Yuezun Li (University at Albany, SUNY)*; Longyin Wen (JD Digit); Ming-Ching Chang (Albany University); Siwei Lyu (University at Albany)
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Paper ID 119 - 3D Gait Recognition Based on a CNN-LSTM Network with the Fusion of SkeGEI and DA Features
Yu Liu (Shanghai Jiao Tong University); Tanfeng Sun (Shanghai Jiao Tong University); Xinghao Jiang (Shanghai Jiao Tong University)*; Ke Xu (Shanghai Jiao Tong University)
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Paper ID 108 - VikingDet: A Real-time Person and Face Detector for Surveillance Cameras
Zhongxia Xiong (Beihang University); Ziying Yao (Beihang University); Yalong Ma (Beihang University); Xinkai Wu (Beihang University)*
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Paper ID 43 - Joint Coarse-and-Fine Semantic Segmentation
Yi-Cheng Chiu (National Central University)*; Chih-Yang Lin (Yuan Ze University); Timothy K. Shih (National Central University, Taiwan)
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Paper ID 117 - Cosine Focal Loss-based Change Detection for Video Surveillance Systems
Jae-Il Jung (Samsung Electronics)*; 준익 장 (Samsung Electronics); 종희 홍 (Samsung) -
Paper ID 29 - Exemplar-based Pseudo-Viewpoint Rotation for White-Cane User Recognition from a 2D Human Pose Sequence
Nishida Naoki (Graduate School of Informatics, Nagoya University)*; Yasutomo Kawanishi (Nagoya University); Daisuke Deguchi (Nagoya University); Ichiro Ide (Nagoya University); Hiroshi Murase (Nagoya University); Jun Piao (NEC Corporation)
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Paper ID 129 - Structural Low-Rank Tracking
Sajid Javed (Khalifa University of Science and Technology)*; Arif Mahmood (Information Technology University); Naoufel Werghi (Khalifa University of Science and Technology); Jorge Manuel Miranda Dias (Khalifa University of Science and Technology)
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Paper ID 102 - Human Pose Estimation for Real-World Crowded Scenarios
Thomas Golda (Karlsruhe Institute of Technology)*
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Paper ID 114 - Improving ResNet-based Feature Extractor for Face Recognition via Re-ranking and Approximate Nearest Neighbor
Sheng-Hsing Hsiao (National Taiwan University)*; Jyh-Shing Roger Jang (National Taiwan University)
Oral V (10:00 to 11:00)
Poster V (11:00 to 12:00)