8 citations · 34 across the 19 of their papers we have counts for
8 papers · 1 filter
End-to-end Training of CNN-CRF via Differentiable Dual-Decomposition
Shaofei Wang, Vishnu Lokhande, Maneesh Singh +2
Modern computer vision (CV) is often based on convolutional neural networks (CNNs) that excel at hierarchical feature extraction. The previous generation of CV approaches was often…
Massively Parallel Benders Decomposition for Correlation Clustering
Margret Keuper, Jovita Lukasik, Maneesh Singh +1
We tackle the problem of graph partitioning for image segmentation using correlation clustering (CC), which we treat as an integer linear program (ILP). We reformulate optimization…
Efficient Multi-Person Pose Estimation with Provable Guarantees
Shaofei Wang, Konrad Paul Kording, Julian Yarkony
Multi-person pose estimation (MPPE) in natural images is key to the meaningful use of visual data in many fields including movement science, security, and rehabilitation. In this p…
Efficient Column Generation for Cell Detection and Segmentation
Chong Zhang, Shaofei Wang, Miguel A. Gonzalez-Ballester +1
We study the problem of instance segmentation in biological images with crowded and compact cells. We formulate this task as an integer program where variables correspond to cells…
Multi-Person Pose Estimation via Column Generation
Shaofei Wang, Chong Zhang, Miguel A. Gonzalez-Ballester +2
We study the problem of multi-person pose estimation in natural images. A pose estimate describes the spatial position and identity (head, foot, knee, etc.) of every non-occluded b…
Exploiting skeletal structure in computer vision annotation with Benders decomposition
Shaofei Wang, Konrad Kording, Julian Yarkony
Many annotation problems in computer vision can be phrased as integer linear programs (ILPs). The use of standard industrial solvers does not to exploit the underlying structure of…