1 citations · 1 across the 9 of their papers we have counts for
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ManiFusion: Unlocking the High-Throughput Generation via Superposition in Manifold Space
Minkyu Kim, Baekseung Kim, Junhoo Lee +2
Diffusion models achieve high-quality image generation but remain computationally expensive due to iterative denoising across many timesteps. Existing acceleration methods mainly r…
VDPP: Video Depth Post-Processing for Speed and Scalability
Daewon Yoon, Injun Baek, Sangyu Han +2
Video depth estimation is essential for providing 3D scene structure in applications ranging from autonomous driving to mixed reality. Current end-to-end video depth models have es…
PedaCo-Gen: Scaffolding Pedagogical Agency in Human-AI Collaborative Video Authoring
Injun Baek, Yearim Kim, Nojun Kwak
While advancements in Text-to-Video (T2V) generative AI offer a promising path toward democratizing content creation, current models are often optimized for visual fidelity rather…
Real-Time Intuitive AI Drawing System for Collaboration: Enhancing Human Creativity through Formal and Contextual Intent Integration
Jookyung Song, Mookyoung Kang, Nojun Kwak
This paper presents a real-time generative drawing system that interprets and integrates both formal intent - the structural, compositional, and stylistic attributes of a sketch -…
MSG Score: Automated Video Verification for Reliable Multi-Scene Generation
Daewon Yoon, Hyeongseok Lee, Wonsik Shin +2
While text-to-video diffusion models have advanced significantly, creating coherent long-form content remains unreliable due to stochastic sampling artifacts. This necessitates gen…