Scene Recognition

35 papers with code • 3 benchmarks • 8 datasets

This task has no description! Would you like to contribute one?

Greatest papers with code

DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition

jetpacapp/DeepBeliefSDK 6 Oct 2013

We evaluate whether features extracted from the activation of a deep convolutional network trained in a fully supervised fashion on a large, fixed set of object recognition tasks can be re-purposed to novel generic tasks.

Domain Adaptation Object Recognition +2

Knowledge Guided Disambiguation for Large-Scale Scene Classification with Multi-Resolution CNNs

yjxiong/caffe 4 Oct 2016

Convolutional Neural Networks (CNNs) have made remarkable progress on scene recognition, partially due to these recent large-scale scene datasets, such as the Places and Places2.

General Classification Scene Classification +1

CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes

leeyeehoo/CSRNet-pytorch CVPR 2018

We demonstrate CSRNet on four datasets (ShanghaiTech dataset, the UCF_CC_50 dataset, the WorldEXPO'10 dataset, and the UCSD dataset) and we deliver the state-of-the-art performance.

Crowd Counting Scene Recognition

CNN Features off-the-shelf: an Astounding Baseline for Recognition

baldassarreFe/deep-koalarization 23 Mar 2014

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.

General Classification Image Classification +3

Fast and Accurate Point Cloud Registration using Trees of Gaussian Mixtures

neka-nat/probreg 6 Jul 2018

Point cloud registration sits at the core of many important and challenging 3D perception problems including autonomous navigation, SLAM, object/scene recognition, and augmented reality.

Autonomous Navigation Point Cloud Registration +1

Deep Filter Banks for Texture Recognition and Segmentation

mcimpoi/deep-fbanks CVPR 2015

Research in texture recognition often concentrates on the problem of material recognition in uncluttered conditions, an assumption rarely met by applications.

Material Recognition Scene Recognition

Bidirectional Projection Network for Cross Dimension Scene Understanding

wbhu/BPNet CVPR 2021

Via the \emph{BPM}, complementary 2D and 3D information can interact with each other in multiple architectural levels, such that advantages in these two visual domains can be combined for better scene recognition.

2D Semantic Segmentation 3D Semantic Segmentation +3

Self-Supervised Model Adaptation for Multimodal Semantic Segmentation

DeepSceneSeg/SSMA 11 Aug 2018

To address this limitation, we propose a mutimodal semantic segmentation framework that dynamically adapts the fusion of modality-specific features while being sensitive to the object category, spatial location and scene context in a self-supervised manner.

Scene Recognition Semantic Segmentation

Local Aggregation for Unsupervised Learning of Visual Embeddings

neuroailab/LocalAggregation-Pytorch ICCV 2019

Unsupervised approaches to learning in neural networks are of substantial interest for furthering artificial intelligence, both because they would enable the training of networks without the need for large numbers of expensive annotations, and because they would be better models of the kind of general-purpose learning deployed by humans.

Object Detection Object Recognition +3

Self-supervised Video Representation Learning by Uncovering Spatio-temporal Statistics

laura-wang/video_repres_mas 31 Aug 2020

Specifically, given an unlabeled video clip, we compute a series of spatio-temporal statistical summaries, such as the spatial location and dominant direction of the largest motion, the spatial location and dominant color of the largest color diversity along the temporal axis, etc.

Action Recognition Representation Learning +2