97 citations · 299 across the 35 of their papers we have counts for
8 papers · 2 filters
Traffic4cast-Traffic Map Movie Forecasting -- Team MIE-Lab
Henry Martin, Ye Hong, Dominik Bucher +2
The goal of the IARAI competition traffic4cast was to predict the city-wide traffic status within a 15-minute time window, based on information from the previous hour. The traffic…
Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wild
Shangzhe Wu, Christian Rupprecht, Andrea Vedaldi
We propose a method to learn 3D deformable object categories from raw single-view images, without external supervision. The method is based on an autoencoder that factors each inpu…
Improving Feature Attribution through Input-specific Network Pruning
Ashkan Khakzar, Soroosh Baselizadeh, Saurabh Khanduja +3
Attributing the output of a neural network to the contribution of given input elements is a way of shedding light on the black-box nature of neural networks. Due to the complexity…
Self-labelling via simultaneous clustering and representation learning
Yuki Markus Asano, Christian Rupprecht, Andrea Vedaldi
Combining clustering and representation learning is one of the most promising approaches for unsupervised learning of deep neural networks. However, doing so naively leads to ill p…
Towards Unsupervised Image Captioning with Shared Multimodal Embeddings
Iro Laina, Christian Rupprecht, Nassir Navab
Understanding images without explicit supervision has become an important problem in computer vision. In this paper, we address image captioning by generating language descriptions…
Photo-Geometric Autoencoding to Learn 3D Objects from Unlabelled Images
Shangzhe Wu, Christian Rupprecht, Andrea Vedaldi
We show that generative models can be used to capture visual geometry constraints statistically. We use this fact to infer the 3D shape of object categories from raw single-view im…