7 papers · 1 filter
Odoriko: A Shape-Aware Multimodal Diffusion Framework for Human Motion
Dongseok Shim, Julian Tanke, Kengo Uchida +5
Human motion generation has been widely studied across diverse input modalities, text, music, and video, and recent efforts have unified these into single multimodal frameworks. Ho…
Echoes Over Time: Unlocking Length Generalization in Video-to-Audio Generation Models
Christian Simon, Masato Ishii, Wei-Yao Wang +8
Scaling multimodal alignment between video and audio is challenging, particularly due to limited data and the mismatch between text descriptions and frame-level video information.…
PTC-Depth: Pose-Refined Monocular Depth Estimation with Temporal Consistency
Leezy Han, Seunggyu Kim, Dongseok Shim +1
Monocular depth estimation (MDE) has been widely adopted in the perception systems of autonomous vehicles and mobile robots. However, existing approaches often struggle to maintain…
EUGens: Efficient, Unified, and General Dense Layers
Sang Min Kim, Byeongchan Kim, Arijit Sehanobish +7
Efficient neural networks are essential for scaling machine learning models to real-time applications and resource-constrained environments. Fully-connected feedforward layers (FFL…
MVLight: Relightable Text-to-3D Generation via Light-conditioned Multi-View Diffusion
Dongseok Shim, Yichun Shi, Kejie Li +2
Recent advancements in text-to-3D generation, building on the success of high-performance text-to-image generative models, have made it possible to create imaginative and richly te…
AURA : Automatic Mask Generator using Randomized Input Sampling for Object Removal
Changsuk Oh, H. Jin Kim
The objective of the image inpainting task is to fill missing regions of an image in a visually plausible way. Recently, deep-learning-based image inpainting networks have generate…