Object Detection In Indoor Scenes
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Benchmarks
SUN RGB-D
Most implemented
Frustum PointNets for 3D Object Detection from RGB-D Data
Papers
Lookalike3D: Seeing Double in 3D
3D object understanding and generation methods produce impressive results, yet they often overlook a pervasive source of information in real-world scenes: repeated objects. We introduce the task of lookalike object detec…
Object Detection In Indoor Scenes3D Object ReconstructionUnified Object Detector for Different Modalities based on Vision Transformers
Traditional systems typically require different models for processing different modalities, such as one model for RGB images and another for depth images. Recent research has demonstrated that a single model for one moda…
Object Detection In Indoor ScenesTransfer LearningsimCrossTrans: A Simple Cross-Modality Transfer Learning for Object Detection with ConvNets or Vision Transformers
Transfer learning is widely used in computer vision (CV), natural language processing (NLP) and achieves great success. Most transfer learning systems are based on the same modality (e.g. RGB image in CV and text in NLP)…
object-detectionObject DetectionObject Detection In Indoor ScenesTransfer LearningFrustum VoxNet for 3D object detection from RGB-D or Depth images
Recently, there have been a plethora of classification and detection systems from RGB as well as 3D images. In this work, we describe a new 3D object detection system from an RGB-D or depth-only point cloud. Our system f…
3D Object DetectionObject DetectionObject Detection In Indoor ScenesThe effect of changing training data on a fixed deep learning detection model
Within the lack of accurate data, for some computer vision applications, researchers usually use other pictures collected from different sources for the training. To know the effect of these added data, we compare the de…
Object DetectionObject Detection In Indoor ScenesFaster Bounding Box Annotation for Object Detection in Indoor Scenes
This paper proposes an approach for rapid bounding box annotation for object detection datasets. The procedure consists of two stages: The first step is to annotate a part of the dataset manually, and the second step pro…
Objectobject-detectionObject DetectionObject Detection In Indoor Scenes