1 citations · 1 across the 6 of their papers we have counts for
6 papers
Controllable Complex Human Motion Video Generation via Text-to-Skeleton Cascades
Ashkan Taghipour, Morteza Ghahremani, Zinuo Li +3
Generating videos of complex human motions such as flips, cartwheels, and martial arts remains challenging for current video diffusion models. Text-only conditioning is temporally…
Conditional Diffusion for 3D CT Volume Reconstruction from 2D X-rays
Martin Rath, Morteza Ghahremani, Yitong Li +3
Computed tomography (CT) provides rich 3D anatomical detail but is often constrained by high radiation exposure, substantial costs, and limited availability. Standard chest X-rays…
SVR-GS: Spatially Variant Regularization for Probabilistic Masks in 3D Gaussian Splatting
Ashkan Taghipour, Vahid Naghshin, Benjamin Southwell +3
3D Gaussian Splatting (3DGS) enables fast, high-quality novel view synthesis but typically relies on densification followed by pruning to optimize the number of Gaussians. Existing…
LatentMove: Towards Complex Human Movement Video Generation
Ashkan Taghipour, Morteza Ghahremani, Mohammed Bennamoun +5
Image-to-video (I2V) generation seeks to produce realistic motion sequences from a single reference image. Although recent methods exhibit strong temporal consistency, they often s…
Faster Image2Video Generation: A Closer Look at CLIP Image Embedding's Impact on Spatio-Temporal Cross-Attentions
Ashkan Taghipour, Morteza Ghahremani, Mohammed Bennamoun +4
This paper investigates the role of CLIP image embeddings within the Stable Video Diffusion (SVD) framework, focusing on their impact on video generation quality and computational…
Box It to Bind It: Unified Layout Control and Attribute Binding in T2I Diffusion Models
Ashkan Taghipour, Morteza Ghahremani, Mohammed Bennamoun +3
While latent diffusion models (LDMs) excel at creating imaginative images, they often lack precision in semantic fidelity and spatial control over where objects are generated. To a…