9 papers
AffineLens: Capturing the Continuous Piecewise Affine Functions of Neural Networks
Yi Wei, Xuan Qi, Furao Shen +3
Piecewise affine neural networks (PANNs) provide a principled geometric perspective on neural network expressivity by characterizing the input--output map as a continuous piecewise…
Training-Time Batch Normalization Reshapes Local Partition Geometry in Piecewise-Affine Networks
Xuan Qi, Yi Wei, Fanqi Yu +3
Batch normalization (BN) is central to modern deep networks, but its effect on the realized function during training remains less understood than its optimization benefits. We stud…
HAC: Parameter-Efficient Hyperbolic Adaptation of CLIP for Zero-Shot VQA
Francesco Dibitonto, Cigdem Beyan, Vittorio Murino
Recent advances in representation learning have shown that hyperbolic geometry can offer a more expressive alternative to the Euclidean embeddings used in CLIP models, capturing hi…
Geometry-Conditioned Diffusion for Occlusion-Robust In-Bed Pose Estimation
Navid Aslankhani Khameneh, Marco Carletti, Cigdem Beyan
Robust in-bed human pose estimation under blanket occlusion remains challenging due to the scarcity of reliable labeled training data for heavily covered poses. Existing approaches…
Discriminator-Guided Adaptive Diffusion for Source-Free Test-Time Adaptation under Image Corruptions
Francesco Olivato, Cigdem Beyan, Vittorio Murino
In this work, we study Source-Free Unsupervised Domain Adaptation under corruption-induced domain shifts, where performance degradation is caused by natural image corruptions that…
Lifelong Imitation Learning with Multimodal Latent Replay and Incremental Adjustment
Fanqi Yu, Matteo Tiezzi, Tommaso Apicella +2
We introduce a lifelong imitation learning framework that enables continual policy refinement across sequential tasks under realistic memory and data constraints. Our approach depa…