6 papers
GeoNVS: Geometry Grounded Video Diffusion for Novel View Synthesis
Minjun Kang, Inkyu Shin, Taeyeop Lee +3
Novel view synthesis requires strong 3D geometric consistency and the ability to generate visually coherent images across diverse viewpoints. While recent camera-controlled video d…
Inference-Time Scaling for Joint Audio-Video Generation
Jaemin Jung, Kyeongha Rho, Inkyu Shin +1
Joint audio-video generation aims to synthesize realistic audio-video pairs that are both semantically aligned with text prompts and precisely synchronized. While existing joint au…
Drag4D: Align Your Motion with Text-Driven 3D Scene Generation
Minjun Kang, Inkyu Shin, Taeyeop Lee +2
We introduce Drag4D, an interactive framework that integrates object motion control within text-driven 3D scene generation. This framework enables users to define 3D trajectories f…
SCORE: Scaling audio generation using Standardized COmposite REwards
Jaemin Jung, Jaehun Kim, Inkyu Shin +1
The goal of this paper is to enhance Text-to-Audio generation at inference, focusing on generating realistic audio that precisely aligns with text prompts. Despite the rapid advanc…
Deeply Supervised Flow-Based Generative Models
Inkyu Shin, Chenglin Yang, Liang-Chieh Chen
Flow based generative models have charted an impressive path across multiple visual generation tasks by adhering to a simple principle: learning velocity representations of a linea…
Enhancing Temporal Consistency in Video Editing by Reconstructing Videos with 3D Gaussian Splatting
Inkyu Shin, Qihang Yu, Xiaohui Shen +3
Recent advancements in zero-shot video diffusion models have shown promise for text-driven video editing, but challenges remain in achieving high temporal consistency. To address t…