9 papers
Dissect and Prune: Enhancing Robustness in AI-Generated Image Detection
Dahye Kim, Jaehyun Choi, Hyun Seok Seong +4
While existing AI-generated image detectors report high performance, we identify that this is largely driven by a critical prediction asymmetry: a bias toward the real class that s…
Learning Neural Deformation Representation for 4D Dynamic Shape Generation
Gyojin Han, Jiwan Hur, Jaehyun Choi +1
Recent developments in 3D shape representation opened new possibilities for generating detailed 3D shapes. Despite these advances, there are few studies dealing with the generation…
Beyond Semantics: Disentangling Information Scope in Sparse Autoencoders for CLIP
Yusung Ro, Jaehyun Choi, Junmo Kim
Sparse Autoencoders (SAEs) have emerged as a powerful tool for interpreting the internal representations of CLIP vision encoders, yet existing analyses largely focus on the semanti…
PRISM: Video Dataset Condensation with Progressive Refinement and Insertion for Sparse Motion
Jaehyun Choi, Jiwan Hur, Gyojin Han +2
Video dataset condensation aims to reduce the immense computational cost of video processing. However, it faces a fundamental challenge regarding the inseparable interdependence be…
Frequency-Aware Token Reduction for Efficient Vision Transformer
Dong-Jae Lee, Jiwan Hur, Jaehyun Choi +2
Vision Transformers have demonstrated exceptional performance across various computer vision tasks, yet their quadratic computational complexity concerning token length remains a s…
DAM: Domain-Aware Module for Multi-Domain Dataset Condensation
Jaehyun Choi, Gyojin Han, Dong-Jae Lee +2
Dataset Condensation (DC) has emerged as a promising solution to mitigate the computational and storage burdens associated with training deep learning models. However, existing DC…