Sub-tile-based grid sampling in neural video codecs
AssigneeIntel Corporation
InventorsPrashant Laddha, Om Ji Omer, Arnab Raha, Deepak Abraham Mathaikutty
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AssigneeIntel Corporation
InventorsPrashant Laddha, Om Ji Omer, Arnab Raha, Deepak Abraham Mathaikutty
Estimating the term…
Real-time neural video codecs face significant latency and energy bottlenecks due to pixel-level grid sampling, which requires irregular, fine-grained memory accesses and limits efficient hardware acceleration. To address this, a sub-tile-based grid sampling technique is disclosed herein. The technique determines super tile sizes using motion vector gradients, neural network parameters, and available on-chip memory. A super tile is split into sub-tiles by detecting motion boundaries through motion vector analysis, where a sub-tile has homogeneous motion vectors. For each sub-tile, a reference bounding box is computed to enable efficient block transfers of reference data, and per-pixel metadata is generated for feature interpolation. The pipelined, parallelizable solution reduces number of memory accesses and computational overhead, compared to existing pixel-based techniques.
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