5 citations · 8 across the 6 of their papers we have counts for
9 papers
Can Video World Models Track Unobserved World States?
Joonghyuk Shin, Yicong Hong, Jaesik Park +1
Video world models are increasingly used as simulators, but visual fidelity alone does not show that a model maintains the hidden state of the world. We examine this difference wit…
Text-based Tactile Graphics Generation for the Visually Impaired
Ruihan Gao, Joonghyuk Shin, Ava Pun +3
Tactile graphics are a primary medium for blind and low-vision (BLV) individuals to access non-textual information. However, they are difficult to scale or personalize. While recen…
Direct Reward Fine-Tuning on Poses for Single Image to 3D Human in the Wild
Seunguk Do, Minwoo Huh, Joonghyuk Shin +1
Single-view 3D human reconstruction has achieved remarkable progress through the adoption of multi-view diffusion models, yet the recovered 3D humans often exhibit unnatural poses.…
MotionStream: Real-Time Video Generation with Interactive Motion Controls
Joonghyuk Shin, Zhengqi Li, Richard Zhang +4
Current motion-conditioned video generation methods suffer from prohibitive latency (minutes per video) and non-causal processing that prevents real-time interaction. We present Mo…
Exploring Multimodal Diffusion Transformers for Enhanced Prompt-based Image Editing
Joonghyuk Shin, Alchan Hwang, Yujin Kim +2
Transformer-based diffusion models have recently superseded traditional U-Net architectures, with multimodal diffusion transformers (MM-DiT) emerging as the dominant approach in st…
JAM-Flow: Joint Audio-Motion Synthesis with Flow Matching
Mingi Kwon, Joonghyuk Shin, Jaeseok Jung +2
The intrinsic link between facial motion and speech is often overlooked in generative modeling, where talking head synthesis and text-to-speech (TTS) are typically addressed as sep…
InstantDrag: Improving Interactivity in Drag-based Image Editing
Joonghyuk Shin, Daehyeon Choi, Jaesik Park
Drag-based image editing has recently gained popularity for its interactivity and precision. However, despite the ability of text-to-image models to generate samples within a secon…
Fill-Up: Balancing Long-Tailed Data with Generative Models
Joonghyuk Shin, Minguk Kang, Jaesik Park
Modern text-to-image synthesis models have achieved an exceptional level of photorealism, generating high-quality images from arbitrary text descriptions. In light of the impressiv…
StudioGAN: A Taxonomy and Benchmark of GANs for Image Synthesis
Minguk Kang, Joonghyuk Shin, Jaesik Park
Generative Adversarial Network (GAN) is one of the state-of-the-art generative models for realistic image synthesis. While training and evaluating GAN becomes increasingly importan…