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20242026
most citedDistilling Diffusion Models into Conditional GANs

2 citations · 2 across the 7 of their papers we have counts for

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5 papers · 1 filter

cs.CV2025

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…

cs.CV2025

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Transformer-based diffusion models have recently superseded traditional U-Net architectures, with multimodal diffusion transformers (MM-DiT) emerging as the dominant approach in st…

cs.AI2025

Tree-Guided Diffusion Planner

Hyeonseong Jeon, Cheolhong Min, Jaesik Park

Planning with pretrained diffusion models has emerged as a promising approach for solving test-time guided control problems. Standard gradient guidance typically performs optimally…

cs.CV2025

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…

cs.CV2025

ISAC: Training-Free Instance-to-Semantic Attention Control for Multi-Instance Generation

Sanghyun Jo, Wooyeol Lee, Ziseok Lee +3

Recent open-weight text-to-image (T2I) diffusion models still struggle with multi-instance prompts, often omitting or merging instances and mixing semantics among similar objects.…