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Beomjun Kim

4 accepted papers

2026

BridgeTA: Bridging the Representation Gap in Knowledge Distillation Via Teacher Assistant for Bird’s Eye View Map Segmentation

ICRA 2026poster

Bird’s Eye View (BEV) map segmentation is one of the most important and challenging tasks in autonomous driving. Camera-only approaches have drawn attention as cost-effective alternatives to LiDAR, but they still fall behind LiDAR-Camera (LC) fusion-based methods. Knowledge Distillation (KD) has bee…

2025

A Computation-Efficient Method of Measuring Dataset Quality based on the Coverage of the Dataset

AISTATS 2025poster

Evaluating dataset quality is an essential task, as the performance of artificial intelligence (AI) systems heavily depends on it. A traditional method for evaluating dataset quality involves training an AI model on the dataset and testing it on a separate test set. However, this approach requires s…

Cited by 0SourceScholar
2025

Peri-LN: Revisiting Normalization Layer in the Transformer Architecture

ICML 2025poster

Selecting a layer normalization (LN) strategy that stabilizes training and speeds convergence in Transformers remains difficult, even for today’s large language models (LLM). We present a comprehensive analytical foundation for understanding how different LN strategies influence training dynamics in…

Cited by 0SourcePDFScholar
2021

Background-Aware Pooling and Noise-Aware Loss for Weakly-Supervised Semantic Segmentation

CVPR 2021poster

We address the problem of weakly-supervised semantic segmentation (WSSS) using bounding box annotations. Although object bounding boxes are good indicators to segment corresponding objects, they do not specify object boundaries, making it hard to train convolutional neural networks (CNNs) for semant…

Cited by 121PDFScholar