Scene Recognition
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Benchmarks
YUP++
AID
MIT Indoor Scenes
Places365
SUN-RGBD
SUN397
ADE20K
ScanNet
Most implemented
CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes
Bilinear CNNs for Fine-grained Visual Recognition
CNN Features off-the-shelf: an Astounding Baseline for Recognition
An Empirical Study of Remote Sensing Pretraining
Papers
A Comparative Study of Label-free Representation Quality Metrics in Deep Learning
We present a comparative study of label-free metrics for assessing the quality of representations in deep neural networks to understand their reliability under a wide variety of configurations. We group existing label-fr…
Scene RecognitionRethinking Text-to-Image as Semantic-Aware Data Augmentation for Indoor Scene Recognition
In the realm of computer vision, indoor image recognition presents challenges due to the intricate interplay of lighting conditions, occlusions, and diverse object arrangements within confined spaces. To address the lack…
Data AugmentationScene RecognitionPairWise Image Finder: An Open-source Tool for Finding Visually Aligned Street-Level Image Pairs for Urban Perception Studies
Change detection and scene recognition techniques have been widely applied to Street View Imagery (SVI) to understand changes in scenes across the years. However, metadata alone is often insufficient to reliably find vis…
Semantic SegmentationScene RecognitionChange DetectionClaimDiff-RL: Fine-Grained Caption Reinforcement Learning through Visual Claim Comparison
Long-form image captioning exposes a reward granularity problem in RL: captions are judged as whole sequences, while the important errors occur at the level of individual visual claims. A good dense caption should be bot…
Reinforcement LearningScene RecognitionImage CaptioningObject CountingBeyond Logit Adjustment: A Residual Decomposition Framework for Long-Tailed Reranking
Long-tailed classification, where a small number of frequent classes dominate many rare ones, remains challenging because models systematically favor frequent classes at inference time. Existing post-hoc methods such as …
Image ClassificationScene RecognitionDynamic Graph Neural Network with Adaptive Features Selection for RGB-D Based Indoor Scene Recognition
Multi-modality of color and depth, i.e., RGB-D, is of great importance in recent research of indoor scene recognition. In this kind of data representation, depth map is able to describe the 3D structure of scenes and geo…
Graph Neural NetworkScene Recognition