3 citations · 4 across the 4 of their papers we have counts for
4 papers
MotionJEPA: Preventing Temporal Feature Collapse by Capturing Visual Changes in Latent Space
Markus Karmann, Shile Li, Christian Internò +10
Joint Embedding Predictive Architectures (JEPAs) are a promising paradigm for learning task-agnostic latent world models without visual reconstruction. However, standard JEPA train…
Joint Post-Training Quantization of Vision Transformers with Learned Prompt-Guided Data Generation
Shile Li, Markus Karmann, Onay Urfalioglu
We present a framework for end-to-end joint quantization of Vision Transformers trained on ImageNet for the purpose of image classification. Unlike prior post-training or block-wis…
Implicit Learning of Scene Geometry from Poses for Global Localization
Mohammad Altillawi, Shile Li, Sai Manoj Prakhya +2
Global visual localization estimates the absolute pose of a camera using a single image, in a previously mapped area. Obtaining the pose from a single image enables many robotics a…
Global Localization: Utilizing Relative Spatio-Temporal Geometric Constraints from Adjacent and Distant Cameras
Mohammad Altillawi, Zador Pataki, Shile Li +1
Re-localizing a camera from a single image in a previously mapped area is vital for many computer vision applications in robotics and augmented/virtual reality. In this work, we ad…