11 papers
Event-guided Neural Video Compression
Jiyun Kong, Jungwoo Kim, Enes Eray Demirtas +2
Neural video codecs derive motion and temporal contexts mainly from RGB frames, leaving room for cross-modal guidance from complementary temporal observations. Event streams can pr…
Mosaic: Compositional Multi-Concept Erasure via Vector Field Blending
Junseok Ko, Jungwoo Kim, Jong-Seok Lee
Concept erasure has emerged as a key research direction for ensuring safe and ethical image synthesis in Text-to-Image (T2I) models. While existing studies have explored concept er…
OmniDrop: Layer-wise Token Pruning for Omni-modal LLMs via Query-Guidance
Yeo Jeong Park, Hyemi Jang, Minseo Choi +3
Omni-modal large language models have demonstrated remarkable potential in holistic multimodal understanding; however, the token explosion caused by high-resolution audio and video…
Coarse-to-Fine: Progressive Image Compression for Semantically Hierarchical Classification
Jungwoo Kim, Jun-Hyuk Kim, Jong-Seok Lee
Recent advances in learned image compression (LIC) have enabled practical deployments, spurring active research into image compression for machines and progressive coding schemes.…
Sparsely-Supervised Data Assimilation via Physics-Informed Schrödinger Bridge
Dohyun Bu, Chanho Kim, Seokun Choi +1
Data assimilation (DA) for systems governed by partial differential equations (PDE) aims to reconstruct full spatiotemporal fields from sparse high-fidelity (HF) observations while…
Steering Away from Memorization: Reachability-Constrained Reinforcement Learning for Text-to-Image Diffusion
Sathwik Karnik, Juyeop Kim, Sanmi Koyejo +2
Text-to-image diffusion models often memorize training data, revealing a fundamental failure to generalize beyond the training set. Current mitigation strategies typically sacrific…
SLIM: Semantic-based Low-bitrate Image compression for Machines
Hyeonjin Lee, Jun-Hyuk Kim, Jong-Seok Lee
In recent years, the demand of image compression models for machine vision has increased dramatically. However, the training frameworks of image compression still focus on the visi…
Event-based Scene Synthesis via Inter-Frame Residual Alignment
Jiyun Kong, Jun-Hyuk Kim, Jong-Seok Lee
Event-based scene synthesis reconstructs target RGB frames from sparse image observations and asynchronous event streams, encompassing both video frame prediction and interpolation…
Progressive Learned Image Compression for Machine Perception
Jungwoo Kim, Jun-Hyuk Kim, Jong-Seok Lee
Recent advances in learned image codecs have extended from human perception toward machine perception However, progressive image compression with fine granular scalability (FGS)-wh…
How Diffusion Models Memorize
Juyeop Kim, Songkuk Kim, Jong-Seok Lee
Despite their success in image generation, diffusion models can memorize training data, raising serious privacy and copyright concerns. Although prior work has sought to characteri…
Exploring Cross-Stage Adversarial Transferability in Class-Incremental Continual Learning
Jungwoo Kim, Jong-Seok Lee
Class-incremental continual learning addresses catastrophic forgetting by enabling classification models to preserve knowledge of previously learned classes while acquiring new one…