Papers with Code · CC BY-SA 4.0

Scene Recognition

3D Character Animation From A Single Photo › Scene Recognition 19 평가 기록 8 datasets

논문

Semantic-Aware Scene Recognition

1909.02410 2019-09-05 이 페이지의 평가 4건

Accuracy: 87.10

FOSNet: An End-to-End Trainable Deep Neural Network for Scene Recognition

1907.07570 2019-07-17 이 페이지의 평가 3건

Accuracy: 90.3

High-order Tensor Pooling with Attention for Action Recognition

2110.05216 2021-10-11 이 페이지의 평가 2건

Accuracy (%): 93.1

A multiple-instance densely-connected ConvNet for aerial scene classification

2020-03-03 이 페이지의 평가 1건

Accuracy: 92.95

All Grains, One Scheme (AGOS): Learning Multi-grain Instance Representation for Aerial Scene Classification

2205.03371 2022-05-06 이 페이지의 평가 1건

Accuracy: 97.43

Hallucinating IDT Descriptors and I3D Optical Flow Features for Action Recognition with CNNs

1906.05910 2019-06-13 이 페이지의 평가 1건

Accuracy (%): 92.6

HalluciNet-ing Spatiotemporal Representations Using a 2D-CNN

1912.04430 2019-12-10 이 페이지의 평가 1건

Accuracy (%): 84.44

Local semantic enhanced convnet for aerial scene recognition

2021-07-08 이 페이지의 평가 1건

Accuracy: 96.36

Omnivore: A Single Model for Many Visual Modalities

2201.08377 2022-01-20 이 페이지의 평가 1건

Accuracy (%): 67.2

Self-Supervised Model Adaptation for Multimodal Semantic Segmentation

1808.03833 2018-08-11 이 페이지의 평가 1건

Average Recall: 54.28

Self-supervising Action Recognition by Statistical Moment and Subspace Descriptors

2001.04627 2020-01-14 이 페이지의 평가 1건

Accuracy (%): 94.4

SRRM: Semantic Region Relation Model for Indoor Scene Recognition

2305.08540 2023-05-15 이 페이지의 평가 1건

10-stage average accuracy: 88.731

When CNNs Meet Random RNNs: Towards Multi-Level Analysis for RGB-D Object and Scene Recognition

2004.12349 2020-04-26 이 페이지의 평가 1건

Accuracy (%): 60.7