arXiv Computer Vision By Jie Deng, Heyang Wang, Changxin Wang, Junkai Shen, Hongyi Chen, Zhiping He, Hongxing Qi, Xudong Zhang, Jianyu Wang

IR275K: A Benchmark for Infrared Multi-Frame Super-Resolution Toward Efficient Remote Sensing

Read the original on arXiv Computer Vision →

The Flow has not summarised this story yet — read it at arXiv Computer Vision.

Hugging Face Trending Papers
Jul 22

Not All Patches are Equal: Sampling Matters for Visible-Infrared Pre-Training

Visible-infrared (VIS-IR) alignment is a key pre-training task for robust multi-sensor perception. Most existing methods use uniform patch-wise contrastive learning, but this can be unreliable in VIS-IR data because imaging-physics differences make some spatially paired regions inherently less comparable, and aligning them with equal strength hinders representation learning and downstream transfer.