2 citations · 2 across the 8 of their papers we have counts for
8 papers
Temporal Self-Distillation: Learning Visual State Tracking in Videos Without Supervision
Shravan Venkatraman, Wenshuai Zhao, Mohammad Hassan Vali +1
We introduce ST (Self-Supervised Self-Distillation over Time), which, to the best of our knowledge, is the first fully self-contained framework for continuous video state track…
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…
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…
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…
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…
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…
Compressing 3D Gaussian Splatting by Noise-Substituted Vector Quantization
Haishan Wang, Mohammad Hassan Vali, Arno Solin
3D Gaussian Splatting (3DGS) has demonstrated remarkable effectiveness in 3D reconstruction, achieving high-quality results with real-time radiance field rendering. However, a key…
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…