mql5

A particularly interesting method entitled CCMR was presented in the paper "CCMR: High Resolution Optical Flow Estimation via Coarse-to-Fine Context-Guided Motion Reasoning". It is an approach to optical flow estimation that combines the advantages of attention-oriented methods of motion aggregation concepts and high-resolution multi-scale approaches. The CCMR method consistently integrates context-based motion grouping concepts into a high-resolution coarse-grained estimation framework. This allows for detailed flow fields that also provide high accuracy in occluded areas. In this context, the authors of the method propose a two-stage motion grouping strategy where global self-attentional contextual features are first computed and them used to guide motion features iteratively across all scales. Thus, context-directed reasoning about XCiT-based motion provides processing at all coarse-grained scales. Experiments conducted by the authors of the method demonstrate the strong performance of the proposed approach and the advantages of its basic concepts.

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