We develop a RGB-D scene recognition model based on object-scene relation(RSBR). First learning a Semantic Network in the semantic domain that classifies the label of a scene on the basis of the labels of all object types. Then, we design an Appearance Network in the appearance domain that recognizes the scene according to local captions. We enforce the Semantic Network to guide the Appearance Network in the learning procedure. Based on the proposed RSBR model, we obtain the state-of-the-art results of RGB-D scene recognition on SUN RGB-D and NYUD2 datasets
Deep learning based object recognition methods have achieved unprecedented success in the recent yea...
Scene understanding is one of the essential and challenging topics in computer vision and photogramm...
Object detection from RGB images is a long-standing problem in image processing and computer vision....
The availability of RGB-D (Kinect-like) cameras has led to an explosive growth of research on robot ...
Scene recognition with RGB images has been extensively studied and has reached very remarkable recog...
Understanding and interacting with one’s environment requires parsing the image of the environment ...
© 2020 IEEE. 3D scene recognition is important for many applications including robotics, autonomous ...
This paper addresses the object recognition problem using multiple-domain inputs. We present a novel...
Scene recognition is a fundamental and open problem in computer vision. It is an essential component...
This paper focuses on the task of RGB-D indoor scene classification. It is a very challenging task d...
A longstanding goal of computer vision is to build a system that can automatically understand a 3D s...
© 1979-2012 IEEE. In this work, we propose a framework for recognizing RGB images or videos by learn...
Recognizing semantic category of objects and scenes captured using vision-based sensors is a challen...
© Springer International Publishing AG 2016. In this paper, we tackle the problem of RGB-D semantic ...
Abstract In this paper, we address the problems of contour detection, bottom-up grouping, object det...
Deep learning based object recognition methods have achieved unprecedented success in the recent yea...
Scene understanding is one of the essential and challenging topics in computer vision and photogramm...
Object detection from RGB images is a long-standing problem in image processing and computer vision....
The availability of RGB-D (Kinect-like) cameras has led to an explosive growth of research on robot ...
Scene recognition with RGB images has been extensively studied and has reached very remarkable recog...
Understanding and interacting with one’s environment requires parsing the image of the environment ...
© 2020 IEEE. 3D scene recognition is important for many applications including robotics, autonomous ...
This paper addresses the object recognition problem using multiple-domain inputs. We present a novel...
Scene recognition is a fundamental and open problem in computer vision. It is an essential component...
This paper focuses on the task of RGB-D indoor scene classification. It is a very challenging task d...
A longstanding goal of computer vision is to build a system that can automatically understand a 3D s...
© 1979-2012 IEEE. In this work, we propose a framework for recognizing RGB images or videos by learn...
Recognizing semantic category of objects and scenes captured using vision-based sensors is a challen...
© Springer International Publishing AG 2016. In this paper, we tackle the problem of RGB-D semantic ...
Abstract In this paper, we address the problems of contour detection, bottom-up grouping, object det...
Deep learning based object recognition methods have achieved unprecedented success in the recent yea...
Scene understanding is one of the essential and challenging topics in computer vision and photogramm...
Object detection from RGB images is a long-standing problem in image processing and computer vision....