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Object Classification

98 papers with code · Computer Vision

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M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network

12 Nov 2018qijiezhao/M2Det

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.

OBJECT CLASSIFICATION OBJECT DETECTION

Events-to-Video: Bringing Modern Computer Vision to Event Cameras

CVPR 2019 uzh-rpg/event-based_vision_resources

Since the output of event cameras is fundamentally different from conventional cameras, it is commonly accepted that they require the development of specialized algorithms to accommodate the particular nature of events.

OBJECT CLASSIFICATION

Contrastive Multiview Coding

ECCV 2020 HobbitLong/CMC

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.

CONTRASTIVE LEARNING OBJECT CLASSIFICATION SELF-SUPERVISED ACTION RECOGNITION SELF-SUPERVISED IMAGE CLASSIFICATION

DeepGCNs: Making GCNs Go as Deep as CNNs

15 Oct 2019lightaime/deep_gcns_torch

This work transfers concepts such as residual/dense connections and dilated convolutions from CNNs to GCNs in order to successfully train very deep GCNs.

NODE CLASSIFICATION OBJECT CLASSIFICATION SEMANTIC SEGMENTATION

And the Bit Goes Down: Revisiting the Quantization of Neural Networks

ICLR 2020 facebookresearch/kill-the-bits

In this paper, we address the problem of reducing the memory footprint of convolutional network architectures.

OBJECT CLASSIFICATION QUANTIZATION

SBNet: Sparse Blocks Network for Fast Inference

CVPR 2018 uber/sbnet

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.

3D OBJECT DETECTION OBJECT CLASSIFICATION SEMANTIC SEGMENTATION

SoundNet: Learning Sound Representations from Unlabeled Video

NeurIPS 2016 cvondrick/soundnet

We learn rich natural sound representations by capitalizing on large amounts of unlabeled sound data collected in the wild.

OBJECT CLASSIFICATION