9 citations · 20 across the 13 of their papers we have counts for
15 papers
Improving Sparse-View 3DGS Generalization via Flat Minima Optimization
Kangmin Seo, Sangeek Hyun, MinKyu Lee +1
Recent advances in neural rendering have established 3D Gaussian Splatting (3DGS) as a highly efficient representation for novel view synthesis, enabling fast training and real-tim…
Cross-scale Aligned Supervision for Training GANs
Sangeek Hyun, MinKyu Lee, Jae-Pil Heo
Modern GANs often introduce adversarial supervision on intermediate generator outputs and interpret the resulting multi-stage synthesis as coarse-to-fine hierarchical generation. I…
Disambiguating 2D-3D Correspondences in Gaussian Splatting-based Feature Fields for Visual Localization
Miso Lee, Sangeek Hyun, Yerim Jeon +1
While Gaussian Splatting-based Feature Fields (GSFFs) have shown promise for visual localization, this paper highlights that photometrically optimized GSFFs are inherently ill-suit…
Looking Beyond the Window: Global-Local Aligned CLIP for Training-free Open-Vocabulary Semantic Segmentation
ByeongCheol Lee, Hyun Seok Seong, Sangeek Hyun +3
A sliding-window inference strategy is commonly adopted in recent training-free open-vocabulary semantic segmentation methods to overcome limitation of the CLIP in processing high-…
SeaCache: Spectral-Evolution-Aware Cache for Accelerating Diffusion Models
Jiwoo Chung, Sangeek Hyun, MinKyu Lee +5
Diffusion models are a strong backbone for visual generation, but their inherently sequential denoising process leads to slow inference. Previous methods accelerate sampling by cac…
Scalable GANs with Transformers
Sangeek Hyun, MinKyu Lee, Jae-Pil Heo
Scalability has driven recent advances in generative modeling, yet its principles remain underexplored for adversarial learning. We investigate the scalability of Generative Advers…
Analyzing the Training Dynamics of Image Restoration Transformers: A Revisit to Layer Normalization
MinKyu Lee, Sangeek Hyun, Woojin Jun +3
This work analyzes the training dynamics of Image Restoration (IR) Transformers and uncovers a critical yet overlooked issue: conventional LayerNorm (LN) drives feature magnitudes…
Fine-Tuning Visual Autoregressive Models for Subject-Driven Generation
Jiwoo Chung, Sangeek Hyun, Hyunjun Kim +3
Recent advances in text-to-image generative models have enabled numerous practical applications, including subject-driven generation, which fine-tunes pretrained models to capture…
Auto-Encoded Supervision for Perceptual Image Super-Resolution
MinKyu Lee, Sangeek Hyun, Woojin Jun +1
This work tackles the fidelity objective in the perceptual super-resolution~(SR). Specifically, we address the shortcomings of pixel-level loss ($\mathcal{L}_\text{pix…
GSGAN: Adversarial Learning for Hierarchical Generation of 3D Gaussian Splats
Sangeek Hyun, Jae-Pil Heo
Most advances in 3D Generative Adversarial Networks (3D GANs) largely depend on ray casting-based volume rendering, which incurs demanding rendering costs. One promising alternativ…
Diversity-aware Channel Pruning for StyleGAN Compression
Jiwoo Chung, Sangeek Hyun, Sang-Heon Shim +1
StyleGAN has shown remarkable performance in unconditional image generation. However, its high computational cost poses a significant challenge for practical applications. Although…
Task-Disruptive Background Suppression for Few-Shot Segmentation
Suho Park, SuBeen Lee, Sangeek Hyun +2
Few-shot segmentation aims to accurately segment novel target objects within query images using only a limited number of annotated support images. The recent works exploit support…
Style Injection in Diffusion: A Training-free Approach for Adapting Large-scale Diffusion Models for Style Transfer
Jiwoo Chung, Sangeek Hyun, Jae-Pil Heo
Despite the impressive generative capabilities of diffusion models, existing diffusion model-based style transfer methods require inference-stage optimization (e.g. fine-tuning or…
Correlation-Guided Query-Dependency Calibration for Video Temporal Grounding
WonJun Moon, Sangeek Hyun, SuBeen Lee +1
Temporal Grounding is to identify specific moments or highlights from a video corresponding to textual descriptions. Typical approaches in temporal grounding treat all video clips…
Query-Dependent Video Representation for Moment Retrieval and Highlight Detection
WonJun Moon, Sangeek Hyun, SangUk Park +2
Recently, video moment retrieval and highlight detection (MR/HD) are being spotlighted as the demand for video understanding is drastically increased. The key objective of MR/HD is…