6 papers
Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking
Soowon Son, Honggyu An, Jisu Nam +7
Despite achieving strong results on standard benchmarks, current point tracking methods rely on feature backbones that are rarely designed with the temporal coherence needed for ro…
TrackCraft3R: Repurposing Video Diffusion Transformers for Dense 3D Tracking
Jisu Nam, Jahyeok Koo, Soowon Son +4
Dense 3D tracking from monocular video is fundamental to dynamic scene understanding. While recent 3D foundation models provide reliable per-frame geometry, recovering object motio…
Pose-dIVE: Pose-Diversified Augmentation with Diffusion Model for Person Re-Identification
Inès Hyeonsu Kim, Woojeong Jin, Soowon Son +6
Person re-identification (Re-ID) often faces challenges due to variations in human poses and camera viewpoints, which significantly affect the appearance of individuals across imag…
TETO: Tracking Events with Teacher Observation for Motion Estimation and Frame Interpolation
Jini Yang, Eunbeen Hong, Soowon Son +4
Event cameras capture per-pixel brightness changes with microsecond resolution, offering continuous motion information lost between RGB frames. However, existing event-based motion…
Emergent Temporal Correspondences from Video Diffusion Transformers
Jisu Nam, Soowon Son, Dahyun Chung +4
Recent advancements in video diffusion models based on Diffusion Transformers (DiTs) have achieved remarkable success in generating temporally coherent videos. Yet, a fundamental q…
Visual Persona: Foundation Model for Full-Body Human Customization
Jisu Nam, Soowon Son, Zhan Xu +6
We introduce Visual Persona, a foundation model for text-to-image full-body human customization that, given a single in-the-wild human image, generates diverse images of the indivi…