7 papers
The Hyperspherical Geometry of CLIP Latent Space: A Semantic Mixture Model
Zijie Yu, Gaowen Liu, Ramana Rao Kompella +2
The paper introduces a probabilistic model for CLIP embeddings using mixtures of von Mises-Fisher distributions on the unit hypersphere, improving density estimation and detection…
LieBN: Batch Normalization over Lie Groups
Ziheng Chen, Yue Song, Rui Wang +2
The paper introduces LieBN, a batch‑normalization framework that works on data lying on Lie groups, providing theoretical control of Riemannian mean and variance across several com…
A Short Note on Batch-efficient Divide-and-Conquer Algorithm for EigenDecomposition
Yue Song
EigenDecomposition (ED) is at the heart of many computer vision algorithms and applications. One crucial bottleneck limiting its usage is the expensive computation cost, particular…
Fast and Stable Riemannian Metrics on SPD Manifolds via Cholesky Product Geometry
Ziheng Chen, Yue Song, Xiao-Jun Wu +1
Recent advances in Symmetric Positive Definite (SPD) matrix learning show that Riemannian metrics are fundamental to effective SPD neural networks. Motivated by this, we revisit th…
A Unified Masked Jigsaw Puzzle Framework for Vision and Language Models
Weixin Ye, Wei Wang, Yahui Liu +5
In federated learning, Transformer, as a popular architecture, faces critical challenges in defending against gradient attacks and improving model performance in both Computer Visi…
The 1st International Workshop on Disentangled Representation Learning for Controllable Generation (DRL4Real): Methods and Results
Qiuyu Chen, Xin Jin, Yue Song +45
This paper reviews the 1st International Workshop on Disentangled Representation Learning for Controllable Generation (DRL4Real), held in conjunction with ICCV 2025. The workshop a…