---
markdown_generated_at: "2026-10-14"
title: "QIF 2022 South Korea"
url: "https://www.qualcomm.com/research/university-relations/innovation-fellowship/2022-south-korea"
description: "Rules and details for the Qualcomm Innovation Fellowship for South Korea in 2022."
canonicalUrl: "https://www.qualcomm.com/research/university-relations/innovation-fellowship/2022-south-korea"
---

# 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

### 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 Kim | Yonsei University |
| QIFK2022_69 | Correlation Verification for Image Retrieval | Seongwon Lee | Yonsei University |
| QIFK2022_76 | Self-Taught Metric Learning without Labels | Sungyeon Kim | POSTECH |
| QIFK2022_83 | WHAT MAKES BETTER AUGMENTATION STRATEGIES? AUGMENT DIFFICULT BUT NOT TOO DIFFERENT | Jaehyung Kim | KAIST |
| QIFK2022_85 | One-Trimap Video Matting | Hongje Seong | Yonsei University |
| QIFK2022_86 | Fast Point Transformer | Chunghyun 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 Segmentation | Sohyun-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 Fields | Yoonwoo-Jeong | POSTECH |

### 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:

[Winners](https://www.qualcomm.com/research/university-relations/innovation-fellowship/winners)

[Finalists](https://www.qualcomm.com/research/university-relations/innovation-fellowship/finalists)