COSMOS-NeRF, a volumetric model that extends the Mip-NeRF 360 architecture by incorporating a supervised semantic channel and a multi-view consensus mechanism, represents a significant advancement in integrating semantic and structural information within three-dimensional environments.
A lightweight boundary-aware learning framework that explicitly models boundary regions during training is proposed, showing that incorporating boundary-aware supervision provides an effective and efficient approach to improving segmentation quality in challenging regions.
Waseem Iqbal, J. Paffenholz· The International Archives o...· 0 citations
A complementary prototype representation framework is proposed, employing three modules to collaboratively improve pseudo-label quality and improves the discriminative ability of confused categories by generating semantically similar sub-category negative samples.
Referring remote sensing image segmentation (RRSIS) aims to segment target ground objects in high-resolution remote sensing imagery according to textual descriptions. Due to complex backgrounds and large-scale variations, accurately aligning linguistic semantics with spatial regions remains a challenging problem. Exist...
Sen Lei, Shuai Li, Xin-Yu Xiao et al.· IEEE Transactions on Geoscie...· 2 citations
This work proposes three learned matching heads: a LightGlue-style attention head with DoubleSoftmax scoring on frozen MASt3R descriptors; a DPT-style multi-scale fusion module that exposes layered spatial detail from the VGGT foundation model before pooling; and a multi-view extension that performs joint self-attentio...
Denis Fatykhoph, Timur Akhtyamov, Konstantin Pakulev et al.· arXiv.org· 0 citations
A lightweight and efficient framework that integrates CLIP and DINO foundation models to address three challenges: semantic misalignment between generic text prompts and RSI-specific visuals; static CAM quality; and incomplete object coverage is proposed.
Xin Li, Nicola Genzano, M. Gianinetto et al.· ISPRS Annals of the Photogra...· 0 citations
DeepChoice is introduced, a lightweight view-weighting module for image-guided 3D semantic segmentation that is sensor-agnostic, requires no meshing, and can be integrated as a replacement for standard multi-view fusion rules.
A. Carreaud, Digre Frinde, Shanci Li et al.· The International Archives o...· 0 citations
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