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Found 5 papers, 3 papers with code
Hierarchical Neural Memory Network for Low Latency Event Processing
Conventional architectures encode entire scene contents at a fixed rate regardless of their temporal characteristics.
Ranked #2 on
Object Detection
on GEN1 Detection
Heterogeneous Grid Convolution for Adaptive, Efficient, and Controllable Computation
This paper proposes a novel heterogeneous grid convolution that builds a graph-based image representation by exploiting heterogeneity in the image content, enabling adaptive, efficient, and controllable computations in a convolutional architecture.
Epipolar-Guided Deep Object Matching for Scene Change Detection
To cope with the difficulty, we introduce a deep graph matching network that establishes object correspondence between an image pair.
Rare Event Detection using Disentangled Representation Learning
The effectiveness of the proposed approach is verified by the quantitative evaluations on four change detection datasets, and the qualitative analysis shows that the proposed method can acquire the representations that disentangle rare events from trivial ones.
Effective Use of Dilated Convolutions for Segmenting Small Object Instances in Remote Sensing Imagery
One of such difficulties is that objects are small and crowded in remote sensing imagery.
