WildFireVQA is a new large-scale visual question answering benchmark that pairs RGB imagery with radiometric thermal measurements for aerial wildfire monitoring across six task categories.
Orb: An efficient alternative to sift or surf
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DINO-VO achieves state-of-the-art monocular visual odometry accuracy and generalization by training a differentiable patch selector together with multi-task features and inverse-depth bundle adjustment.
SING3R-SLAM adds submap-level global alignment and reconstruction priors to a Gaussian map to reduce drift and improve local geometry in monocular indoor SLAM.
citing papers explorer
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WildFireVQA: A Large-Scale Radiometric Thermal VQA Benchmark for Aerial Wildfire Monitoring
WildFireVQA is a new large-scale visual question answering benchmark that pairs RGB imagery with radiometric thermal measurements for aerial wildfire monitoring across six task categories.
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DINO-VO: Learning Where to Focus for Enhanced State Estimation
DINO-VO achieves state-of-the-art monocular visual odometry accuracy and generalization by training a differentiable patch selector together with multi-task features and inverse-depth bundle adjustment.
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SING3R-SLAM: Submap-based Indoor Monocular Gaussian SLAM with 3D Reconstruction Priors
SING3R-SLAM adds submap-level global alignment and reconstruction priors to a Gaussian map to reduce drift and improve local geometry in monocular indoor SLAM.