Auto-Rectify Network for Unsupervised Indoor Depth Estimation
Single-View depth estimation using the CNNs trained from unlabelled videos has shown significant promise. However, excellent results have mostly been obtained in street-scene driving scenarios, and…
SOLO : A Simple Framework for Instance Segmentation
Compared to many other dense prediction tasks, e.g., semantic segmentation, it is the arbitrary number of instances that has made instance segmentation much more challenging. In order to predict a …
ABCNet v2 : Adaptive Bezier-Curve Network for Real-Time End-to-End Text Spotting
End-to-end text-spotting, which aims to integrate detection and recognition in a unified framework, has attracted increasing attention due to its simplicity of the two complimentary tasks. It remai…
Virtual Normal : Enforcing Geometric Constraints for Accurate and Robust Dept…
Monocular depth prediction plays a crucial role in understanding 3D scene geometry. Although recent methods have achieved impressive progress in the evaluation metrics such as the pixel-wise relati…
Towards End-to-End Text Spotting in Natural Scenes
Text spotting in natural scene images is of great importance for many image understanding tasks. It includes two sub-tasks: text detection and recognition. In this work, we propose a unified networ…
Effective Training of Convolutional Neural Networks With Low-Bitwidth Weights…
This paper tackles the problem of training a deep convolutional neural network of both low-bitwidth weights and activations. Optimizing a low-precision network is very challenging due to the non-di…
PAN++ : Towards Efficient and Accurate End-to-End Spotting of Arbitrarily-Sha…
Scene text detection and recognition have been well explored in the past few years. Despite the progress, efficient and accurate end-to-end spotting of arbitrarily-shaped text remains challenging. …
FCOS : A Simple and Strong Anchor-Free Object Detector
In computer vision, object detection is one of most important tasks, which underpins a few instance-level recognition tasks and many downstream applications. Recently one-stage methods have gained …
Plenty is Plague : Fine-Grained Learning for Visual Question Answering
Visual Question Answering (VQA) has attracted extensive research focus recently. Along with the ever-increasing data scale and model complexity, the enormous training cost has become an emerging ch…
Ordered or Orderless : A Revisit for Video Based Person Re-Identification
Is recurrent network really necessary for learning a good visual representation for video based person re-identification (VPRe-id)? In this paper, we first show that the common practice of employin…
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