QIF 2022 South Korea

2022 South Korea Program Details

Qualcomm Technologies, Inc. proudly announces the launch of Qualcomm Innovation Fellowship 2022 Korea program.
The program is a qualified paper scholarship selection program and open to Master or PhD students at specific universities in South Korea.

Winners
Finalist
Program Information
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QIF Korea 2022

Jan 18, 2023 | 2:47

2022 South Korea Winners

Application Number Paper Title Student(s) University
QIFK2022_1 TOWARDS CONTINUAL KNOWLEDGE LEARNING OF LANGUAGE MODELS Joel Jang KAIST
QIFK2022_25 UBoCo : Unsupervised Boundary Contrastive Learning for Generic Event Boundary Detection Hyolim Kang, Jinwoo KimYonsei University
QIFK2022_69Correlation Verification for Image Retrieval Seongwon Lee Yonsei University
QIFK2022_76 Self-Taught Metric Learning without LabelsSungyeon Kim POSTECH
QIFK2022_83 WHAT MAKES BETTER AUGMENTATION STRATEGIES? AUGMENT DIFFICULT BUT NOT TOO DIFFERENT Jaehyung Kim KAIST
QIFK2022_85 One-Trimap Video MattingHongje SeongYonsei University
QIFK2022_86 Fast Point TransformerChunghyun Park POSTECH
QIFK2022_88 FINE Samples for Learning with Noisy Labels Taehyeon Kim, Jongwoo Ko KAIST
QIFK2022_90 FIFO: Learning Fog-invariant Features for Foggy Scene SegmentationSohyun-Lee POSTECH
QIFK2022_91 Time Is MattEr: Temporal Self-supervision for Video Transformers Sukmin Yun KAIST
QIFK2022_96 ReSTR: Convolution-free Referring Image Segmentation Using Transformers Namyup-Kim POSTECH
QIFK2022_103 Combating Label Distribution Shift for Active Domain Adaptation Sehyun Hwang POSTECH
QIFK2022_105 From Noisy Prediction to True Label: Noisy Prediction Calibration via Generative Model HeeSun Bae, Seungjae Shin KAIST
QIFK2022_111 PartGlot: Learning Shape Part Segmentation from Language Reference Games Juil Koo KAIST
QIFK2022_114 Learning Semantic Segmentation from Multiple Datasets with Label Shifts Dongwan Kim Seoul National University
QIFK2022_118 MM-TTA: Multi-Modal Test-Time Adaptation for 3D Semantic Segmentation Inkyu Shin KAIST
QIFK2022_123 Transformers Generalize DeepSets and Can be Extended to Graphs and Hypergraphs Jinwoo Kim KAIST
QIFK2022_130 CLIP-Actor: Text-Driven Recommendation and Stylization for Animating Human Meshes Kim Youwang, Kim Ji-Yeon POSTECH
QIFK2022_138 Style Neophile: Constantly Seeking Novel Styles for Domain Generalization Juwon-Kang POSTECH
QIFK2022_144 Self-Calibrating Neural Radiance FieldsYoonwoo-JeongPOSTECH

Fellowship Winners and Finalists

The Qualcomm Innovation Fellowship began in 2009, and has continued to grow with the addition of more universities, more candidates, and expansion to our research centers internationally. Take a look at a list of all our fellowship winners and finalists from years past:

Qualcomm relentlessly innovates to deliver intelligent computing everywhere, helping the world tackle some of its most important challenges. Our leading-edge AI, high performance, low-power computing, and unrivaled connectivity deliver proven solutions that transform major industries. At Qualcomm, we are engineering human progress.

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