Search Results for author: Hyungmin Kim

Found 4 papers, 2 papers with code

ContextMix: A context-aware data augmentation method for industrial visual inspection systems

1 code implementation18 Jan 2024 Hyungmin Kim, Donghun Kim, Pyunghwan Ahn, Sungho Suh, Hansang Cho, Junmo Kim

With the minimal additional computation cost of image resizing, ContextMix enhances performance compared to existing augmentation techniques.

Data Augmentation Object Recognition

Proxy Anchor-based Unsupervised Learning for Continuous Generalized Category Discovery

1 code implementation ICCV 2023 Hyungmin Kim, Sungho Suh, Daehwan Kim, Daun Jeong, Hansang Cho, Junmo Kim

Existing methods for novel category discovery are limited by their reliance on labeled datasets and prior knowledge about the number of novel categories and the proportion of novel samples in the batch.

Class Incremental Learning Incremental Learning +1

SPADE: Sparse Pillar-based 3D Object Detection Accelerator for Autonomous Driving

no code implementations12 May 2023 Minjae Lee, Seongmin Park, Hyungmin Kim, Minyong Yoon, Janghwan Lee, Jun Won Choi, Nam Sung Kim, Mingu Kang, Jungwook Choi

3D object detection using point cloud (PC) data is essential for perception pipelines of autonomous driving, where efficient encoding is key to meeting stringent resource and latency requirements.

3D Object Detection Autonomous Driving +2

AI-KD: Adversarial learning and Implicit regularization for self-Knowledge Distillation

no code implementations20 Nov 2022 Hyungmin Kim, Sungho Suh, SungHyun Baek, Daehwan Kim, Daun Jeong, Hansang Cho, Junmo Kim

Our model not only distills the deterministic and progressive knowledge which are from the pre-trained and previous epoch predictive probabilities but also transfers the knowledge of the deterministic predictive distributions using adversarial learning.

Self-Knowledge Distillation

Cannot find the paper you are looking for? You can Submit a new open access paper.