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Found 6 papers, 2 papers with code
Training-Free Neural Matte Extraction for Visual Effects
Alpha matting is widely used in video conferencing as well as in movies, television, and social media sites.
SimPose: Effectively Learning DensePose and Surface Normals of People from Simulated Data
Additionally, we present our model's 3D surface normal predictions on the MSCOCO dataset that lacks any real 3D surface normal labels.
MoDeep: A Deep Learning Framework Using Motion Features for Human Pose Estimation
In this work, we propose a novel and efficient method for articulated human pose estimation in videos using a convolutional network architecture, which incorporates both color and motion features.
Joint Training of a Convolutional Network and a Graphical Model for Human Pose Estimation
This paper proposes a new hybrid architecture that consists of a deep Convolutional Network and a Markov Random Field.
Learning Human Pose Estimation Features with Convolutional Networks
This paper introduces a new architecture for human pose estimation using a multi- layer convolutional network architecture and a modified learning technique that learns low-level features and higher-level weak spatial models.
Pose-Sensitive Embedding by Nonlinear NCA Regression
We apply our method to challenging real-world data and show that it can generalize beyond hand localization to infer a more general notion of body pose.
