7 papers
Smol-GS: Compact Representations for Abstract 3D Gaussian Splatting
Haishan Wang, Mohammad Hassan Vali, Arno Solin
We present Smol-GS, a novel method for learning compact representations for 3D Gaussian Splatting (3DGS). Our approach learns highly efficient splat-wise features to model 3D space…
DiVeQ: Differentiable Vector Quantization Using the Reparameterization Trick
Mohammad Hassan Vali, Tom Bäckström, Arno Solin
Vector quantization is common in deep models, yet its hard assignments block gradients and hinder end-to-end training. We propose DiVeQ, which treats quantization as adding an erro…
Self-Attention Decomposition For Training Free Diffusion Editing
Tharun Anand, Mohammad Hassan Vali, Arno Solin +2
Diffusion models achieve remarkable fidelity in image synthesis, yet precise control over their outputs for targeted editing remains challenging. A key step toward controllability…
Sparsely Supervised Diffusion
Wenshuai Zhao, Zhiyuan Li, Yi Zhao +5
Diffusion models have shown remarkable success across a wide range of generative tasks. However, they often suffer from spatially inconsistent generation, arguably due to the inher…
Privacy Disclosure of Similarity Rank in Speech and Language Processing
Tom Bäckström, Mohammad Hassan Vali, My Nguyen +1
Speaker, author, and other biometric identification applications often compare a sample's similarity to a database of templates to determine the identity. Given that data may be no…
Unsupervised Panoptic Interpretation of Latent Spaces in GANs Using Space-Filling Vector Quantization
Mohammad Hassan Vali, Tom Bäckström
Generative adversarial networks (GANs) learn a latent space whose samples can be mapped to real-world images. Such latent spaces are difficult to interpret. Some earlier supervised…