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Found 4 papers, 3 papers with code
AdaFocusV3: On Unified Spatial-temporal Dynamic Video Recognition
Recent research has revealed that reducing the temporal and spatial redundancy are both effective approaches towards efficient video recognition, e. g., allocating the majority of computation to a task-relevant subset of frames or the most valuable image regions of each frame.
AdaFocus V2: End-to-End Training of Spatial Dynamic Networks for Video Recognition
Recent works have shown that the computational efficiency of video recognition can be significantly improved by reducing the spatial redundancy.
Instance Segmentation of Biological Images Using Harmonic Embeddings
We present a new instance segmentation approach tailored to biological images, where instances may correspond to individual cells, organisms or plant parts.
Instance Segmentation by Deep Coloring
We propose a new and, arguably, a very simple reduction of instance segmentation to semantic segmentation.
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