Render for CNN: Viewpoint Estimation in Images Using CNNs Trained with Rendered 3D Model Views

This paper proposes a Fast Region-based Convolutional Network method (Fast R-CNN) for object detection. Fast R-CNN builds on previous work to efficiently classify object proposals using deep convolutional networks. Compared to previous work, Fast R-CNN ...

Due to the lack of rotation invariance in traditional convolution operations, even acting a slight rotation on the input can severely degrade the performance of Convolutional Neural Networks (CNNs). To address this, we propose a Rotation-...

• We propose RIC-C: a novel convolutional operation naturally invariant to all input center rotations, no extra parameters or data augmentation.
• Without data augmentation, RIC-CNN shows superior performance on MNIST compared to previous ...

Owing to the flexible architectures of deep convolutional neural networks (CNNs) are successfully used for image denoising. However, they suffer from the following drawbacks: (i) deep network architecture is very difficult to train. (ii) Deeper networks ...