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MLR-APPL-IP-3: Machine learning for image processing 3

Session Type: Poster

Time: Tuesday, September 21, 08:00 - 09:30

Location: Area F

Session Chair: Xin Ding, UBC

MLR-APPL-IP-3.1: HIERARCHICAL REGION PROPOSAL REFINEMENT NETWORK FOR WEAKLY SUPERVISED OBJECT DETECTION

Ming Zhang; University of Electronic Science and Technology of China

Shuaicheng Liu; University of Electronic Science and Technology of China

Bing Zeng; University of Electronic Science and Technology of China

MLR-APPL-IP-3.2: DEEP SENSOR FUSION BASED ON FRUSTUM POINT SINGLE SHOT MULTIBOX DETECTOR FOR 3D OBJECT DETECTION

Yu Wang; Harbin Institute of Technology

Ye Zhang; Harbin Institute of Technology

Shaohua Zhai; Harbin Institute of Technology

Hao Chen; Harbin Institute of Technology

Shaoqi Shi; Harbin Institute of Technology

Gang Wang; Alibaba Group

MLR-APPL-IP-3.3: MULTI-SCALE GRAPH CONVOLUTIONAL INTERACTION NETWORK FOR SALIENT OBJECT DETECTION

Wenqi Che; Shanghai University

Luoyi Sun; Shanghai University

Zhifeng Xie; Shanghai University

Youdong Ding; Shanghai University

Kaili Han; Shanghai University

MLR-APPL-IP-3.4: MULTISCALE IOU: A METRIC FOR EVALUATION OF SALIENT OBJECT DETECTION WITH FINE STRUCTURES

Azim Ahmadzadeh; Georgia State University

Dustin J. Kempton; Georgia State University

Yang Chen; Georgia State University

Rafal A. Angryk; Georgia State University

MLR-APPL-IP-3.5: SGE NET: VIDEO OBJECT DETECTION WITH SQUEEZED GRU AND INFORMATION ENTROPY MAP

Rui Su; Waseda University

Wenjing Huang; Waseda University

Haoyu Ma; University of California, Irvine

Xiaowei Song; Southeast University

Jinglu Hu; Waseda University

MLR-APPL-IP-3.6: PROVABLE TRANSLATIONAL ROBUSTNESS FOR OBJECT DETECTION WITH CONVOLUTIONAL NEURAL NETWORKS

Axel Vierling; Technische Universität Kaiserslautern

Charu James; Technische Universität Kaiserslautern

Nikoletta Katsaouni; Goethe University Frankfurt am Main

Karsten Berns; Technische Universität Kaiserslautern

MLR-APPL-IP-3.7: EFFECTIVE FEATURE FUSION NETWORK IN BIFPN FOR SMALL OBJECT DETECTION

Jun Chen; China University of Geosciences, Wuhan

HongSheng Mai; China University of Geosciences, Wuhan

Linbo Luo; China University of Geosciences, Wuhan

Xiaoqiang Chen; China University of Geosciences, Wuhan

Kangle Wu; China University of Geosciences, Wuhan

MLR-APPL-IP-3.8: OBJECT DETECTION AND AUTOENCODER-BASED 6D POSE ESTIMATION FOR HIGHLY CLUTTERED BIN PICKING

Timon Höfer; University of Tuebingen

Faranak Shamsafar; University of Tuebingen

Nuri Benbarka; University of Tuebingen

Andreas Zell; University of Tuebingen

MLR-APPL-IP-3.9: HUMAN VISION-LIKE ROBUST OBJECT RECOGNITION

Peng Kang; Northwestern University

Hao Hu; University of British Columbia

Srutarshi Banerjee; Northwestern University

Henry Chopp; Northwestern University

Aggelos K. Katsaggelos; Northwestern University

Oliver Cossairt; Northwestern University

MLR-APPL-IP-3.10: TRAINING AN EMBEDDED OBJECT DETECTOR FOR INDUSTRIAL SETTINGS WITHOUT REAL IMAGES

Julia Cohen; Université Lyon 2 - LIRIS (CNRS)

Carlos Crispim-Junior; Université Lyon 2 - LIRIS (CNRS)

Jean-Marc Chiappa; DEMS

Laure Tougne; Université Lyon 2 - LIRIS (CNRS)

MLR-APPL-IP-3.11: SEMI-SUPERVISED OBJECT DETECTION WITH SPARSELY ANNOTATED DATASET

Jihun Yoon; hutom

Seungbum Hong; hutom

Min-Kook Choi; hutom

MLR-APPL-IP-3.12: PSEUDO-LABEL GENERATION-EVALUATION FRAMEWORK FOR CROSS DOMAIN WEAKLY SUPERVISED OBJECT DETECTION

Shengxiong Ouyang; Zhejiang University

Xinglu Wang; Zhejiang University

Kejie Lyu; Zhejiang University

Yingming Li; Zhejiang University

MLR-APPL-IP-3.13: BOTTOM-UP SALIENCY MEETS TOP-DOWN SEMANTICS FOR OBJECT DETECTION

Tomoya Sawada; Mitsubishi Electric Corporation

Teng-Yok Lee; Mitsubishi Electric Corporation

Masahiro Mizuno; Mitsubishi Electric Corporation

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

My ICIP 2021 Schedule

MLR-APPL-IP-3: Machine learning for image processing 3