From the 1 of 5 linked papers with an AI index.
5 papers
Controlling Motion Transfer in Diffusion Transformers via Attention Heads
Sunyoung Jung, Jiwoo Park, Yoonseok Choi +3
The paper studies how individual attention heads in diffusion transformer models handle motion and spatial structure, and introduces a head-aware method to control motion transfer…
QWERTY: Training-Free Motion Control via Query-Warped Video Diffusion Transformers
Kyobin Choo, Youngmin Kim, Hyunkyung Han +4
Video diffusion transformers (DiTs) generate high-fidelity and temporally coherent videos, yet motion control remains implicit, primarily relying on text prompts. As a result, achi…
Anatomically Consistent TMJ Disc Segmentation via Semantic Anchoring and Clinical Priors
Dayun Ju, Chanyoung Kim, Sunyoung Jung +4
Segmenting the temporomandibular joint (TMJ) disc from MRI is essential for accurate diagnosis of internal derangement, yet it remains unreliable in practice due to its small size,…
Interpreting vision transformers via residual replacement model
Jinyeong Kim, Junhyeok Kim, Yumin Shim +3
How do vision transformers (ViTs) represent and process the world? This paper addresses this long-standing question through the first systematic analysis of 6.6K features across al…
Deformation-Aware Segmentation Network Robust to Motion Artifacts for Brain Tissue Segmentation using Disentanglement Learning
Sunyoung Jung, Yoonseok Choi, Mohammed A. Al-masni +2
Motion artifacts caused by prolonged acquisition time are a significant challenge in Magnetic Resonance Imaging (MRI), hindering accurate tissue segmentation. These artifacts appea…