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20202026
most citedFeature Extraction for Hyperspectral Imagery: The Evolution from Shallow to Deep (Overview and Toolbox)

537 citations · 795 across the 13 of their papers we have counts for

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6 papers · 1 filter

cs.AI2026

Dual-Domain Manifold Modeling for Hyperspectral Image Fusion

Chengxin Xie, Qiya Song, Yangbangyan Jiang +2

Achieving a coherent integration of spectral richness and spatial fidelity remains a central objective in hyperspectral image fusion. However, existing hyperspectral image fusion m…

cs.CV2026

Multimodal Large Language Models for Remote Sensing Image Understanding: Domain-Specific or General-Purpose?

Qiwei Ma, Chunping Qiu, Xinjun Cheng +5

The rapid development of multimodal large language models (MLLMs) has introduced a flexible paradigm for remote sensing image scene understanding (RSISU), enabling natural-language…

cs.CV2026

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

Qiwei Ma, Bin Deng, Junjie Zhu +5

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 b…

cs.CV2026

Report of the 5th PVUW Challenge: Towards More Diverse Modalities in Pixel-Level Understanding

Chang Liu, Henghui Ding, Nikhila Ravi +40

This report summarizes the objectives, datasets, and top-performing methodologies of the 2026 Pixel-level Video Understanding in the Wild (PVUW) Challenge, hosted at CVPR 2026, whi…

cs.CV2026

2nd of the 5th PVUW MeViS-Audio Track: ASR-SaSaSa2VA

Zhiyu Wang, Xudong Kang, Shutao Li

Audio-based video object segmentation aims to locate and segment objects in videos conditioned on audio cues, requiring precise understanding of both appearance and motion. Recent…

cs.CV2026

Robust Remote Sensing Image-Text Retrieval with Noisy Correspondence

Qiya Song, Yiqiang Xie, Yuan Sun +2

As a pivotal task that bridges remote visual and linguistic understanding, Remote Sensing Image-Text Retrieval (RSITR) has attracted considerable research interest in recent years.…