Object Detection In Indoor Scenes
4 papers with code • 1 benchmarks • 10 datasets
Object detection in indoor scenes is the task of performing object detection within an indoor environment.
( Image credit: Faster Bounding Box Annotation for Object Detection in Indoor Scenes )
Datasets
- SUN RGB-D
- Kitchen Scenes
- ISOD
- Transparent Object Images | Indoor Object Dataset
- Stairs Image Dataset | Parts of House | Indoor
- Mobile Phone Dataset | Smartphone & Feature Phone
- Suitcase/Luggage Dataset Indoor Object Image
- Masks Dataset | Unattended Mask Images
- Electronics Object Image Dataset | Computer Parts
- Bottles and Cups Dataset | Household Objects
Most implemented papers
Frustum PointNets for 3D Object Detection from RGB-D Data
In this work, we study 3D object detection from RGB-D data in both indoor and outdoor scenes.
simCrossTrans: A Simple Cross-Modality Transfer Learning for Object Detection with ConvNets or Vision Transformers
Most transfer learning systems are based on the same modality (e. g. RGB image in CV and text in NLP).
Learning Rich Features from RGB-D Images for Object Detection and Segmentation
In this paper we study the problem of object detection for RGB-D images using semantically rich image and depth features.
Unified Object Detector for Different Modalities based on Vision Transformers
We evaluate our unified model on the SUN RGB-D dataset, and demonstrate that it achieves similar or better performance in terms of mAP50 compared to state-of-the-art methods in the SUNRGBD16 category, and comparable performance in point cloud only mode.