Awards
Best Paper Award and Best Student Paper Award
These awards are intended to recognize exceptional contributions and encourage new entrants into the fields within the technical scope of the conference. Winners will be selected using paper reviews and additional study by an Awards Committee. Two papers will be selected for the Best Paper Award and three for the Best Student Paper Award. Winners receive a cash prize (split among authors for the Best Paper Award and among student authors for the Best Student Paper Award) and a certificate. The award will be presented during IEEE ICIP 2019, and also announced on the conference website.
Best Paper and Best Student Paper* Finalists
|
Session |
Title |
|
TP.L8.1 |
IMAGE DENOISING WITH GRAPH-CONVOLUTIONAL NEURAL NETWORKS |
|
|
Diego Valsesia; Politecnico di Torino Giulia Fracastoro; Politecnico di Torino Enrico Magli; Politecnico di Torino |
|
TA.L5.1 |
LEARNING TO RENDER BETTER IMAGE PREVIEWS |
|
|
Shumeet Baluja; Google Inc. David Marwood; Google Inc. Nick Johnston; Google Inc. Michele Covell; Google Inc. |
|
WQ.PB.6 |
EXTENDING LBP AND CONVOLUTION-LIKE OPERATIONS ON THE MESH* |
|
|
Claudio Tortorici; Khalifa University Stefano Berretti; University of Florence |
|
WA.L1.4 |
ADAPTIVE INFERENCE USING HIERARCHICAL CONVOLUTIONAL BAG-OF-FEATURES FOR LOW-POWER EMBEDDED PLATFORMS |
|
|
Nikolaos Passalis; Tampere University Jenni Raitoharju; Tampere University Anastasios Tefas; Aristotle University of Thessaloniki Moncef Gabbouj; Tampere University |
|
MA.PA.4 |
CONTINUOUS SIGN LANGUAGE RECOGNITION VIA REINFORCEMENT LEARNING* |
|
|
Zhihao Zhang; University of Science and Technology of China |
|
TA.L9.5 |
BLAST-NET: SEMANTIC SEGMENTATION OF HUMAN BLASTOCYST COMPONENTS VIA CASCADED ATROUS PYRAMID AND DENSE PROGRESSIVE UPSAMPLING* |
|
|
Reza Moradi Rad; Simon Fraser University Parvaneh Saeedi; Simon Fraser University Jason Au; Pacific Centre for Reproductive Medicine Jon Havelock; Pacific Centre for Reproductive Medicine |
|
TA.PH.2 |
UPDCNN: A NEW SCHEME FOR IMAGE UPSAMPLING AND DEBLURRING USING A DEEP CONVOLUTIONAL NEURAL NETWORK* |
|
|
Alireza Esmaeilzehi; Concordia University M. Omair Ahmad; Concordia University M.N.S. Swamy; Concordia University |
|
MA.L6.2 |
UNCONSTRAINED FLOOD EVENT DETECTION USING ADVERSARIAL DATA AUGMENTATION* |
|
|
Samira Pouyanfar; Florida International University Yudong Tao; University of Miami Saad Sadiq; University of Miami Haiman Tian; Florida International University Yuexuan Tu; University of Miami Tianyi Wang; Florida International University Shu-Ching Chen; Florida International University Mei-Ling Shyu; University of Miami |
|
WA.L7.1 |
DETECTING GENERATED IMAGE BASED ON A COUPLED NETWORK WITH TWO-STEP PAIRWISE LEARNING* |
|
|
Yi-Xiu Zhuang; National Pingtung University Science and Technology Chih-Chung Hsu; National Pingtung University Science and Technology |
|
TQ.PE.4 |
HIGH JOINT SPECTRAL-SPATIAL RESOLUTION IMAGING VIA NANOSTRUCTURED RANDOM BROADBAND FILTERING |
|
|
Xiaolin Wu; McMaster University Dahua Gao; Xidian University Qin Chen; Suzhou Institute of Nano-Tech and Nano-Bionics Kaiwei Zhang; Xidian University |
|
MA.PC.6 |
ESTIMATING THE SPATIAL RESOLUTION OF OVERHEAD IMAGERY USING CONVOLUTIONAL NEURAL NETWORKS* |
|
|
Haolin Liang; University of California, Merced Shawn Newsam; University of California, Merced |
|
TA.PG.2 |
UNDERWATER IMAGE SYNTHESIS FROM RGB-D IMAGES AND ITS APPLICATION TO DEEP UNDERWATER IMAGE RESTORATION* |
|
|
Takumi Ueda; Tokyo University of Agriculture and Technology Koki Yamada; Tokyo University of Agriculture and Technology Yuichi Tanaka; Tokyo University of Agriculture and Technology |
|
MQ.L5.2 |
LOW-COMPLEXITY TRANSFORM ADJUSTMENTS FOR VIDEO CODING |
|
|
Amir Said; Qualcomm Technologies, Inc. Hilmi Egilmez; Qualcomm Technologies, Inc. Yung-Hsuan Chao; Qualcomm Technologies, Inc. |
|
WA.L6.3 |
DEEP OBJECTIVE ASSESSMENT MODEL BASED ON SPATIO-TEMPORAL PERCEPTION OF 360-DEGREE VIDEO FOR VR SICKNESS PREDICTION* |
|
|
Kihyun Kim; Korea Advanced Institute of Science and Technology (KAIST) Sangmin Lee; Korea Advanced Institute of Science and Technology (KAIST) Hak Gu Kim; Korea Advanced Institute of Science and Technology (KAIST) Minho Park; Korea Advanced Institute of Science and Technology (KAIST) Yong Man Ro; Korea Advanced Institute of Science and Technology (KAIST) |
|
WP.L5.4 |
LIGHT FIELD COMPRESSION USING FOURIER DISPARITY LAYERS* |
|
|
Elian Dib; INRIA Mikael Le Pendu; Trinity College Dublin Christine Guillemot; INRIA |
|
TP.L5.5 |
DESIGNING RECURRENT NEURAL NETWORKS BY UNFOLDING AN L1-L1 MINIMIZATION ALGORITHM* |
|
|
Hung Duy Le; Vrije Universiteit Brussel-imec Huynh Van Luong; Vrije Universiteit Brussel-imec Nikos Deligiannis; Vrije Universiteit Brussel-imec |
|
TP.L5.6 |
EXACT INCREMENTAL AND DECREMENTAL LEARNING FOR LS-SVM |
|
|
Wei-Han Lee; IBM Research Bong Jun Ko; IBM Research Shiqiang Wang; IBM Research Changchang Liu; IBM Research Kin Leung; Imperial College London |
|
MQ.L5.1 |
IMPROVED QUANTIZATION AND TRANSFORM COEFFICIENT CODING FOR THE EMERGING VERSATILE VIDEO CODING (VVC) STANDARD |
|
|
Heiko Schwarz; Fraunhofer Heinrich Hertz Institute / FU Berlin Tung Nguyen; Fraunhofer Heinrich Hertz Institute Detlev Marpe; Fraunhofer Heinrich Hertz Institute Thomas Wiegand; Fraunhofer Heinrich Hertz Institute / TU Berlin Marta Karczewicz; Qualcomm Inc. Muhammed Coban; Qualcomm Inc. Jie Dong; Qualcomm Inc. |
|
TP.PF.8 |
DISTORTED REPRESENTATION SPACE CHARACTERIZATION THROUGH BACKPROPAGATED GRADIENTS* |
|
|
Gukyeong Kwon; Georgia Institute of Technology Mohit Prabhushankar; Georgia Institute of Technology Dogancan Temel; Georgia Institute of Technology Ghassan AlRegib; Georgia Institute of Technology |
|
TA.L5.2 |
MULTI-TASK LEARNING WITH COMPRESSIBLE FEATURES FOR COLLABORATIVE INTELLIGENCE* |
|
|
Saeed Ranjbar Alvar; Simon Fraser University Ivan V. Bajic; Simon Fraser University |
Best Paper Award for Industry
The Best Paper Award for Industry will be given to author(s) of an ICIP 2019 paper exhibiting exceptional industrial merit and potential industrial impact within the technical scope of the conference. The candidate(s) are not required to be IEEE members or to be working in industry. The prize shall consist of a monetary amount and a certificate. The award will be presented during IEEE ICIP 2019, and also announced on the conference website. The award will not be conferred in case no suitable candidates can be identified.
Best Industry Paper Finalists
|
Session |
Title |
|
TA.L5.1 |
LEARNING TO RENDER BETTER IMAGE PREVIEWS |
|
|
Shumeet Baluja; Google Inc. David Marwood; Google Inc. Nick Johnston; Google Inc. Michele Covell; Google Inc. |
|
MQ.L5.2 |
LOW-COMPLEXITY TRANSFORM ADJUSTMENTS FOR VIDEO CODING |
|
|
Amir Said; Qualcomm Technologies, Inc. Hilmi Egilmez; Qualcomm Technologies, Inc. Yung-Hsuan Chao; Qualcomm Technologies, Inc. |
|
WQ.L6.1 |
5D VIDEO STABILIZATION THROUGH SENSOR VISION FUSION |
|
|
Binnan Zhuang; xsense.ai Dongwoon Bai; Samsung Semiconductor Inc Jungwon Lee; Samsung Semiconductor Inc |
|
WA.L5.2 |
INTERWEAVED PREDICTION FOR AFFINE MOTION COMPENSATION |
|
|
Kai Zhang; Bytedance Inc. Li Zhang; Bytedance Inc. Hongbin Liu; Bytedance Inc. Jizheng Xu; Bytedance Inc. Yue Wang; Bytedance Inc. |