SOTAVerified

Scene Recognition

Papers

Showing 150 of 207 papers

TitleStatusHype
An Empirical Study of Remote Sensing PretrainingCode2
On the Road with GPT-4V(ision): Early Explorations of Visual-Language Model on Autonomous DrivingCode2
Omnivore: A Single Model for Many Visual ModalitiesCode2
A Study of Face Obfuscation in ImageNetCode1
NEVIS'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision ResearchCode1
MultiScene: A Large-scale Dataset and Benchmark for Multi-scene Recognition in Single Aerial ImagesCode1
BORM: Bayesian Object Relation Model for Indoor Scene RecognitionCode1
Where in the World is this Image? Transformer-based Geo-localization in the WildCode1
Deep Attentional Structured Representation Learning for Visual RecognitionCode1
When CNNs Meet Random RNNs: Towards Multi-Level Analysis for RGB-D Object and Scene RecognitionCode1
Cross-Task Transfer for Geotagged Audiovisual Aerial Scene RecognitionCode1
Object-to-Scene: Learning to Transfer Object Knowledge to Indoor Scene RecognitionCode1
NuScenes-MQA: Integrated Evaluation of Captions and QA for Autonomous Driving Datasets using Markup AnnotationsCode1
Stochastic Partial Swap: Enhanced Model Generalization and Interpretability for Fine-Grained RecognitionCode1
PIR: Remote Sensing Image-Text Retrieval with Prior Instruction Representation LearningCode1
Unsupervised Model Personalization while Preserving Privacy and Scalability: An Open ProblemCode1
Visual Memorability for Robotic Interestingness via Unsupervised Online LearningCode1
NarrativeXL: A Large-scale Dataset For Long-Term Memory ModelsCode1
CoMAE: Single Model Hybrid Pre-training on Small-Scale RGB-D DatasetsCode1
Indoor Scene Recognition in 3DCode1
A Prior Instruction Representation Framework for Remote Sensing Image-text RetrievalCode1
Self-supervised Video Representation Learning by Uncovering Spatio-temporal StatisticsCode1
MovieCLIP: Visual Scene Recognition in MoviesCode1
Bidirectional Projection Network for Cross Dimension Scene UnderstandingCode1
A multiple-instance densely-connected ConvNet for aerial scene classificationCode0
Aerial Scene Understanding in The Wild: Multi-Scene Recognition via Prototype-based Memory NetworksCode0
Ambiguity-Aware Multi-Object Pose Optimization for Visually-Assisted Robot ManipulationCode0
Advancing ALS Applications with Large-Scale Pre-training: Dataset Development and Downstream AssessmentCode0
Local semantic enhanced convnet for aerial scene recognitionCode0
Object Detectors Emerge in Deep Scene CNNsCode0
All Grains, One Scheme (AGOS): Learning Multi-grain Instance Representation for Aerial Scene ClassificationCode0
A Retention-Centric Framework for Continual Learning with Guaranteed Model Developmental SafetyCode0
Knowledge Guided Disambiguation for Large-Scale Scene Classification with Multi-Resolution CNNsCode0
HalluciNet-ing Spatiotemporal Representations Using a 2D-CNNCode0
Learning From Less Data: A Unified Data Subset Selection and Active Learning Framework for Computer VisionCode0
Empirical Analysis of Foundational Distinctions in Linked Open DataCode0
CNN Features off-the-shelf: an Astounding Baseline for RecognitionCode0
Classifying Variable-Length Audio Files with All-Convolutional Networks and Masked Global PoolingCode0
AGA: Attribute-Guided AugmentationCode0
From Volcano to Toyshop: Adaptive Discriminative Region Discovery for Scene RecognitionCode0
DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic LandslidesCode0
DisasterNets: Embedding Machine Learning in Disaster MappingCode0
Learning image representations tied to ego-motionCode0
Deep Filter Banks for Texture Recognition and SegmentationCode0
An embarrassingly simple comparison of machine learning algorithms for indoor scene classificationCode0
InstaIndoor and Multi-modal Deep Learning for Indoor Scene RecognitionCode0
Capsule Networks as Generative ModelsCode0
AGA: Attribute Guided AugmentationCode0
Counting Manatee Aggregations using Deep Neural Networks and Anisotropic Gaussian KernelCode0
Depth CNNs for RGB-D scene recognition: learning from scratch better than transferring from RGB-CNNsCode0
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