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Point cloud is an important type of geometric data structure.
#2 best model for Scene Segmentation on ScanNet
Compared to YOLOv2 on the MS-COCO object detection, ESPNetv2 delivers 4. 4% higher accuracy with 6x fewer FLOPs.
#26 best model for Object Detection on PASCAL VOC 2007
Finally, we gather up the decoder layers with equivalent scales (sizes) to develop a feature pyramid for object detection, in which every feature map consists of the layers (features) from multiple levels.
#30 best model for Object Detection on COCO test-dev
We analyze key properties of the approach that make it work, finding that the contrastive loss outperforms a popular alternative based on cross-view prediction, and that the more views we learn from, the better the resulting representation captures underlying scene semantics.
#11 best model for Self-Supervised Action Recognition on UCF101
In this paper, we address the problem of reducing the memory footprint of convolutional network architectures.
This work transfers concepts such as residual/dense connections and dilated convolutions from CNNs to GCNs in order to successfully train very deep GCNs.
#2 best model for Semantic Segmentation on S3DIS
We learn rich natural sound representations by capitalizing on large amounts of unlabeled sound data collected in the wild.
Conventional deep convolutional neural networks (CNNs) apply convolution operators uniformly in space across all feature maps for hundreds of layers - this incurs a high computational cost for real-time applications.
We present OctNet, a representation for deep learning with sparse 3D data.
We report on a series of experiments conducted for different recognition tasks using the publicly available code and model of the \overfeat network which was trained to perform object classification on ILSVRC13.