Start Over Filtering by: "Reconstruction via a structured resultant matrix" CVPR 2012 Li Wang Zhang Kim Lee Remove constraint "Reconstruction via a structured resultant matrix" CVPR …

Dec 12, 2025 · Self-supervised pre-training has revolutionized foundation models for languages, individual 2D images and videos, but remains largely unexplored for learning 3D-aware …

We propose an inno-vative MRI reconstruction framework that employs struc-tured state space models at its core, aimed at amplifying both long-range contextual sensitivity and …

During the reconstruction process, the measured object is affected by its own reflection, environmental illumination, and other factors, resulting in a large number of mismatching …

With advancements in deep neural networks and substantial training data, this field has seen dramatic developments and diverse applications, ranging from augmented reality to …

Oct 9, 2025 · On-the-fly 3D reconstruction from monocular image sequences is a long-standing challenge in computer vision, critical for applications such as real-to-sim, AR/VR, and robotics.

Jan 1, 2024 · Start Over Filtering by:"Reconstruction via a structured resultant matrix" CVPR 2012 paperRemove constraint "Reconstruction via a structured resultant matrix" CVPR 2012 …

In this dissertation, I develop strategies to enable robots to quickly and automatically make decisions about what data to collect in complex real-world conditions to improve learned …

Filtering by: "Reconstruction via a structured resultant matrix" CVPR 2012 Li Wang Zhang Kim Lee Remove constraint "Reconstruction via a structured resultant matrix" CVPR 2012 Li Wang …

Super-resolution (SR) has become one of the most critical problems in image and video processing. In Chapter 2 of this thesis, a detailed review of existing Deep Learning (DL) …