Sergey Karayev

I am a PhD candidate in CS at UC Berkeley, working with Trevor Darrell as part of the BVLC.
I want to solve hard problems in artificial intelligence, particularly for computer vision.
More details are in my CV. I look like this.


  • Recognition on a Budget

    Features have different costs and different classes benefit from different features. A multi-class recognition system should dynamically select them to maximize performance under a cost budget.

  • Depth-informed Object Detection

    Using the Microsoft Kinect, we gather a large dataset of indoor crowded scenes. We investigate ways to unify state-of-the-art object detection systems and improve them with depth information.

  • Probabilistic Local Image Features

    Our method for additively decomposing local image patches, LDA-SIFT, shows best performance on a novel transparent object recognition dataset. We recursively extend the model to multiple layers and successfully apply it to general object classification.

  • Image Style

    Image style is an important part of visual communication, but has received scant research attention. We present novel datasets, including of painting style. Our approach is based on convolutional nets and shows excellent classification and search.

  • Rayleigh: Multi-color image search

    We present an open-source system for quickly searching large image collections by multiple colors given as a palette, or by color similarity to a query image.

  • CabFriendly

    A cloud-based mobile web application to match up users who request similar trips and would like to share a cab. The application is hosted on EC2 and combines several open-source frameworks with social networking and location-awareness APIs.