1 citations · 1 across the 6 of their papers we have counts for
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Task-Induced Riemannian Metrics for Vision Transformer Feature Spaces
Andrew Bond, Ege Erdem Özlü, Tuna Çimen +4
Methods operating on Vision Transformer (ViT) feature spaces typically rely on Euclidean distance or cosine similarity. This assumes that every direction is equally meaningful, but…
Beyond Gaussian Bottlenecks: Topologically Aligned Encoding of Vision-Transformer Feature Spaces
Andrew Bond, Ilkin Umut Melanlioglu, Erkut Erdem +1
Modern visual world modeling systems increasingly rely on high-capacity architectures and large-scale data to produce plausible motion, yet they often fail to preserve underlying 3…
GaussianVideo: Efficient Video Representation via Hierarchical Gaussian Splatting
Andrew Bond, Jui-Hsien Wang, Long Mai +2
Efficient neural representations for dynamic video scenes are critical for applications ranging from video compression to interactive simulations. Yet, existing methods often face…
VidStyleODE: Disentangled Video Editing via StyleGAN and NeuralODEs
Moayed Haji Ali, Andrew Bond, Tolga Birdal +4
We propose , a spatiotemporally continuous disentangled eo representation based upon GAN and Neural-s. Effective t…