4 accepted papers
The miniaturization of thermal sensors for mobile platforms inherently limits their spatial resolution and textural fidelity, leading to blurry and less informative images. Existing thermal super-resolution (SR) methods can be grouped into single-image and RGB-guided approaches: the former struggles
Metalenses offer significant potential for ultra-compact computational imaging but face challenges from complex optical degradation and computational restoration difficulties. Existing methods typically rely on precise optical calibration or massive paired datasets, which are non-trivial for real-wo…
Compressive spectral image reconstruction is a critical method for acquiring images with high spatial and spectral resolution. Current advanced methods which involve designing deeper networks or adding more self-attention modules are limited by the scope of attention modules and the irrelevance of a…
We present PANDA, the first gigaPixel-level humAN-centric viDeo dAtaset, for large-scale, long-term, and multi-object visual analysis. The videos in PANDA were captured by a gigapixel camera and cover real-world scenes with both wide field-of-view ( 1 square kilometer area) and high-resolution detai…