Fine-Grained Head Pose Estimation Without Keypoints

Estimating the head pose of a person is a crucial problem that has a large amount of applications such as aiding in gaze estimation, modeling attention, fitting 3D models to video and performing face alignment. Traditionally head pose is computed by estimating some keypoints from the target face and solving the 2D to 3D correspondence problem with a mean human head model. We argue that this is a fragile method because it relies entirely on landmark detection performance, the extraneous head model and an ad-hoc fitting step. We present an elegant and robust way to determine pose by training a multi-loss convolutional neural network on 300W-LP, a large synthetically expanded dataset, to predict intrinsic Euler angles (yaw, pitch and roll) directly from image intensities through joint binned pose classification and regression. We present empirical tests on common in-the-wild pose benchmark datasets which show state-of-the-art results. Additionally we test our method on a dataset usually used for pose estimation using depth and start to close the gap with state-of-the-art depth pose methods. We open-source our training and testing code as well as release our pre-trained models.Comment: Accepted to Computer Vision and Pattern Recognition Workshops (CVPRW), 2018 IEEE Conference on. IEEE, 201

Snow’s Argument Cultures: From clashing contexts to heterogeneous solidarity

Understood as an analysis of clashing argument cultures, C. P. Snow’s “Two Cultures” illuminates challenges to interdisciplinarity. Argument cultures involve not only distinct styles of argumentation and background assumptions, but also emotional attitudes and prejudices, including disdain for other argument cultures, that rest on ideals of inquiry and society. Case studies suggest that fruitful interdisciplinary work across such cultures requires institutionalized boundary contexts in which heterogeneous solidarity can develop

Argumentation Theory and the Recent Philosophy of Science

The thesis of my paper is that argumentation theory provides a promising heuristic framework for addressing issues raised by the rationality debates in the philosophy of science, in particular the issues connected with scientific controversies over the appraisal and choice of competing theories. The first part of the paper grounds this thesis historically. In criticizing the logical empiricists, Thomas Kuhn set the stage for the subsequent opposition between a normative, anti-sociological philosophy of science and a descriptive, anti-philosophical sociology of knowledge. But he also hinted at the main lines of a multi-dimensional theory of argumentation which might frame a wide range of current investigations into scientific reasoning. In the second part of the paper I focus on the central normative aspect of this framework, dialectical argumentation, and clarify the key challenge, the underdetermination of theories by evidence. In the third part, I attempt to get beyond the dichotomy informing the rationality debates by reformulating the problem of theory choice within a broader context of scientific rationality