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  1. The standard maritime obstacle detection evaluation pro-tocol MODS [5] is applied to analyze the methods based on semantic segmentation. This protocol considers three se-mantic classes: …

  2. MODS is a spher-ical view synthesis method that renders novel views from an Omnidirectional Stereo (ODS) input pair. We adapted MODS to work with a pair of ERPs as input, like in our …

  3. The subchallenges were based on the SeaDronesSee and MODS benchmarks. This report summarizes the main findings of the individual subchallenges and introduces a new …

  4. Abstract Continual learning can empower vision-language mod-els to continuously acquire new knowledge, without the need for access to the entire historical dataset. However, mitigating the …

  5. Abstract Since the advent of Multimodal Large Language Mod-els (MLLMs), they have made a significant impact across a wide range of real-world applications, particularly in Autonomous …

  6. MODS [29] investigated this line of work by introducing an iterative scheme to generate intermediate synthetic views between images. MODS also proposed an adaptive system to …

  7. Abstract Accurate acquisition of surface meteorological conditions at arbitrary locations holds significant importance for weather forecasting and climate simulation. Meteorologi-cal states …

  8. It is now possible to replace simple point correspon-dences with affine-covariant feature detectors, such as ASIFT [27] and MODS [26]. Such an affine correspon-dence (AC) consists of a point …

  9. EVD [9] dataset was de-veloped for evaluating MODS (Matching On Demand with view Synthesis), an algorithm for wide-baseline matching of outdoor scenes but only includes …

  10. tailed context information following motion com-pens tion. Consequently, we set a larger channel number of 128. Additionally, we report the complexity of the BiShift-Mods i both the motion …