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20242026
most citedDeep Optics for Video Snapshot Compressive Imaging

15 citations · 16 across the 10 of their papers we have counts for

collaborators

11 papers

cs.CV2026

GSCI: Robust Gaussian Splatting For Snapshot Compressive Imaging via Large Vision Model Priors

Yanming Yang, Chenxi Song, Ping Wang +2

Snapshot Compressive Imaging (SCI) offers an efficient solution for high-speed video acquisition and, under exposure-time camera--scene relative motion, multi-view scene capture by…

cs.CV2026

Coloring the Noise: Adversarial Sobolev Alignment for Faithful Image Super Resolution

Hongbo Wang, Huaibo Huang, Pin Wang +3

Generative priors in Image Super-Resolution (SR) often compromise faithful restoration, we attribute this limitation to a fundamental spectral misalignment between isotropic object…

cs.CV2026

Deep Probabilistic Unfolding for Quantized Compressive Sensing

Gang Qu, Ping Wang, Siming Zheng +1

We propose a deep probabilistic unfolding model to address the classical quantized compressive sensing problem that leverages an unfolding framework to enhance the reconstruction a…

cs.CV2026

Tuning Real-World Image Restoration at Inference: A Test-Time Scaling Paradigm for Flow Matching Models

Purui Bai, Junxian Duan, Pin Wang +4

Although diffusion-based real-world image restoration (Real-IR) has achieved remarkable progress, efficiently leveraging ultra-large-scale pre-trained text-to-image (T2I) models an…

cs.CV2026

PolarAPP: Beyond Polarization Demosaicking for Polarimetric Applications

Yidong Luo, Chenggong Li, Yunfeng Song +4

Polarimetric imaging enables advanced vision applications such as normal estimation and de-reflection by capturing unique surface-material interactions. However, existing applicati…

cs.CV2025

High-Speed FHD Full-Color Video Computer-Generated Holography

Haomiao Zhang, Miao Cao, Xuan Yu +6

Computer-generated holography (CGH) is a promising technology for next-generation displays. However, generating high-speed, high-quality holographic video requires both high frame…

cs.CV2025★ 1 cited

Physics-guided Deep Unfolding Network for Enhanced Kronecker Compressive sensing

Gang Qu, Ping Wang, Siming Zheng +1

Deep networks have achieved remarkable success in image compressed sensing (CS) task, namely reconstructing a high-fidelity image from its compressed measurement. However, existing…

cs.CV2024

Hierarchical Separable Video Transformer for Snapshot Compressive Imaging

Ping Wang, Yulun Zhang, Lishun Wang +1

Transformers have achieved the state-of-the-art performance on solving the inverse problem of Snapshot Compressive Imaging (SCI) for video, whose ill-posedness is rooted in the mix…

cs.CV2024★ 15 cited

Deep Optics for Video Snapshot Compressive Imaging

Ping Wang, Lishun Wang, Xin Yuan

Video snapshot compressive imaging (SCI) aims to capture a sequence of video frames with only a single shot of a 2D detector, whose backbones rest in optical modulation patterns (a…

cs.CV2024

Dual-Scale Transformer for Large-Scale Single-Pixel Imaging

Gang Qu, Ping Wang, Xin Yuan

Single-pixel imaging (SPI) is a potential computational imaging technique which produces image by solving an illposed reconstruction problem from few measurements captured by a sin…

eess.IV2024

SCINeRF: Neural Radiance Fields from a Snapshot Compressive Image

Yunhao Li, Xiaodong Wang, Ping Wang +2

In this paper, we explore the potential of Snapshot Compressive Imaging (SCI) technique for recovering the underlying 3D scene representation from a single temporal compressed imag…