Despite the recent success of deep neural networks, it remains challenging to effectively model the long-tail class distribution in visual recognition tasks. To address this problem, we first investigate the performance bottleneck of the two-stage …

Capturing long-range dependencies in feature representations is crucial for many visual recognition tasks. Despite recent successes of deep convolutional networks, it remains challenging to model non-local context relations between visual features. A …

We present an efficient scene layout aware object detection method for traffic surveillance. Given an input image, our approach first estimates its scene layout by transferring object annotations in a large dataset to the target image based on …

Generating object proposals has become a key component of modern object detection pipelines. However, most existing methods generate the object candidates independently of each other. In this paper, we present an approach to co-generating object …

This paper presents a context-aware object proposal generation method for stereo images. Unlike existing methods which mostly rely on image-based or depth features to generate object candidates, we propose to incorporate additional geometric and …