• Publications
  • Influence
Deep Image Matting
A novel deep learning based algorithm that can tackle image matting problems when an image has similar foreground and background colors or complicated textures and evaluation results demonstrate the superiority of this algorithm over previous methods.
Video Object Segmentation Using Space-Time Memory Networks
This work proposes a novel solution for semi-supervised video object segmentation by leveraging memory networks and learning to read relevant information from all available sources to better handle the challenges such as appearance changes and occlussions.
YouTube-VOS: A Large-Scale Video Object Segmentation Benchmark
A new large-scale video object segmentation dataset called YouTube Video Object Segmentation dataset (YouTube-VOS) is built which aims to establish baselines for the development of new algorithms in the future.
A wireless sensor network For structural monitoring
Wisden incorporates two novel mechanisms, reliable data transport using a hybrid of end-to-end and hop-by-hop recovery, and low-overhead data time-stamping that does not require global clock synchronization.
Deep Interactive Object Selection
This paper presents a novel deep-learning-based algorithm which has much better understanding of objectness and can reduce user interactions to just a few clicks and is superior to all existing interactive object selection approaches.
Slimmable Neural Networks
This work presents a simple and general method to train a single neural network executable at different widths, permitting instant and adaptive accuracy-efficiency trade-offs at runtime, and demonstrates better performance of slimmable models compared with individual ones across a wide range of applications.
YouTube-VOS: Sequence-to-Sequence Video Object Segmentation
This work builds a new large-scale video object segmentation dataset called YouTube Video Object Segmentation dataset (YouTube-VOS) and proposes a novel sequence-to-sequence network to fully exploit long-term spatial-temporal information in videos for segmentation.
Wide Activation for Efficient and Accurate Image Super-Resolution
This report demonstrates that with same parameters and computational budgets, models with wider features before ReLU activation have significantly better performance for single image super-resolution (SISR) and introduces linear low-rank convolution into SR networks to achieve even better accuracy-efficiency tradeoffs.
Object segmentation using graph cuts based active contours
  • N. Xu, R. Bansal, N. Ahuja
  • Mathematics, Computer Science
    IEEE Computer Society Conference on Computer…
  • 18 June 2003
A graph cuts based active contours (GCBAC) approach to object segmentation problems that uses graph cuts to iteratively deform the contour and has the ability to jump over local minima and provide a more global result.
Parallel subgraph listing in a large-scale graph
A novel parallel subgraph listing framework, named PSgL, which completely relies on the graph traversal, and avoids the explicit join operation, and proves the problem of partial subgraph instance distribution for workload balance is NP-hard, and carefully design a set of heuristic strategies.