Results 151 to 160 of about 1,596,426 (191)

Sparse reconstruction for radar

SPIE Proceedings, 2008
Imaging is not itself a system goal, but is rather a means to support inference tasks. For data processing with linearized signal models, we seek to report all high-probability interpretations of the data and to report confidence labels in the form of posterior probabilities.
Lee C. Potter, Philip Schniter, Justin Ziniel   +2 more
openaire   +1 more source

High-Resolution ISAR Imaging and Motion Compensation With 2-D Joint Sparse Reconstruction

IEEE Transactions on Geoscience and Remote Sensing, 2020
With regard to the multifunction radar transmitting sparse stepped-frequency-modulation (SSFM) signal for inverse synthetic aperture radar (ISAR) imaging, the received echo signal is usually sparse in two dimensions, i.e., sparse stepped-frequency ...
Shuai Shao, Lei Zhang, Hongwei Liu
semanticscholar   +1 more source

NeuSurf: On-Surface Priors for Neural Surface Reconstruction from Sparse Input Views

AAAI Conference on Artificial Intelligence, 2023
Recently, neural implicit functions have demonstrated remarkable results in the field of multi-view reconstruction. However, most existing methods are tailored for dense views and exhibit unsatisfactory performance when dealing with sparse views. Several
Han Huang, Yulun Wu, Junsheng Zhou, G. Gao, M. Gu, Yu-Shen Liu   +5 more
semanticscholar   +1 more source

InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models

arXiv.org
We present InstantMesh, a feed-forward framework for instant 3D mesh generation from a single image, featuring state-of-the-art generation quality and significant training scalability.
Jiale Xu, Weihao Cheng, Yiming Gao, Xintao Wang, Shenghua Gao, Ying Shan   +5 more
semanticscholar   +1 more source

Sparse correlation kernel reconstruction

1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258), 1999
This paper presents a new paradigm for signal reconstruction and superresolution, correlation kernel analysis (CKA), that is based on the selection of a sparse set of bases from a large dictionary of class-specific basis functions. The basis functions that we use are the correlation functions of the class of signals we are analyzing.
C. Papageorgiou, F. Girosi, T. Poggio
openaire   +1 more source

Jumping Ahead: Improving Reconstruction Fidelity with JumpReLU Sparse Autoencoders

arXiv.org
Sparse autoencoders (SAEs) are a promising unsupervised approach for identifying causally relevant and interpretable linear features in a language model's (LM) activations.
Senthooran Rajamanoharan, Tom Lieberum, Nicolas Sonnerat, Arthur Conmy, Vikrant Varma, János Kramár, Neel Nanda   +6 more
semanticscholar   +1 more source

Generalized Widely Linear Robust Adaptive Beamforming: A Sparse Reconstruction Perspective

IEEE Transactions on Aerospace and Electronic Systems
Widely linear (WL) robust adaptive beamforming exhibits superior performance by effectively leveraging the additional noncircularity information. However, existing studies focus solely on the noncircular (NC) impinging interferences, often overlooking ...
Yaxing Yue, Zongyu Zhang, Zhiguo Shi
semanticscholar   +1 more source

MV-DUSt3R+: Single-Stage Scene Reconstruction from Sparse Views In 2 Seconds

Computer Vision and Pattern Recognition
Recent sparse multi-view scene reconstruction advances like DUSt3R and MASt3R no longer require camera calibration and camera pose estimation. However, they only process a pair of views at a time to infer pixel-aligned pointmaps.
Zhenggang Tang, Yuchen Fan, Dilin Wang, Hongyu Xu, Rakesh Ranjan, Alexander G. Schwing, Zhicheng Yan   +6 more
semanticscholar   +1 more source

SplatFields: Neural Gaussian Splats for Sparse 3D and 4D Reconstruction

European Conference on Computer Vision
Digitizing 3D static scenes and 4D dynamic events from multi-view images has long been a challenge in computer vision and graphics. Recently, 3D Gaussian Splatting (3DGS) has emerged as a practical and scalable reconstruction method, gaining popularity ...
Marko Mihajlovic, Sergey Prokudin, Siyu Tang, Robert Maier, Federica Bogo, Tony Tung, Edmond Boyer   +6 more
semanticscholar   +1 more source

Video super-resolution via pre-frame constrained and deep-feature enhanced sparse reconstruction

Pattern Recognition, 2020
This paper presents a new video super-resolution (SR) method that can generate high-quality and temporally coherent high-resolution (HR) videos. Starting from the traditional sparse reconstruction framework that works well for image SR, we improve it ...
Qiuxia Lai, Yongwei Nie, Hanqiu Sun, Qiang Xu, Zhensong Zhang, Mingyu Xiao   +5 more
semanticscholar   +1 more source