Research Area
Year Published

104 Results

September 10, 2018

Dense Pose Transfer

European Conference on Computer Vision (ECCV)

In this work we integrate ideas from surface-based modeling with neural synthesis: we propose a combination of surface-based pose estimation and deep generative models that allows us to perform accurate pose transfer, i.e. synthesize a new image of a person based on a single image of that person and the image of a pose donor.

By: Natalia Neverova, Riza Alp Guler, Iasonas Kokkinos

September 9, 2018

Graph R-CNN for Scene Graph Generation

European Conference on Computer Vision (ECCV)

We propose a novel scene graph generation model called Graph R-CNN, that is both effective and efficient at detecting objects and their relations in images.

By: Jianwei Yang, Jiasen Lu, Stefan Lee, Dhruv Batra, Devi Parikh

September 9, 2018

DDRNet: Depth Map Denoising and Refinement for Consumer Depth Cameras Using Cascaded CNNs

European Conference on Computer Vision (ECCV)

Although plenty of progresses have been made to reduce the noises and boost geometric details, due to the inherent illness and the real-time requirement, the problem is still far from been solved. We propose a cascaded Depth Denoising and Refinement Network (DDRNet) to tackle this problem by leveraging the multi-frame fused geometry and the accompanying high quality color image through a joint training strategy.

By: Shi Yan, Chenglei Wu, Lizhen Wang, Feng Xu, Liang An, Kaiwen Guo, Yebin Liu

September 9, 2018

Multi-Fiber Networks for Video Recognition

European Conference on Computer Vision (ECCV)

In this paper, we aim to reduce the computational cost of spatio-temporal deep neural networks, making them run as fast as their 2D counterparts while preserving state-of-the-art accuracy on video recognition benchmarks.

By: Yunpeng Chen, Yannis Kalantidis, Jianshu Li, Shuicheng Yan, Jiashi Feng

September 9, 2018

Deep Clustering for Unsupervised Learning of Visual Features

European Conference on Computer Vision (ECCV)

In this work, we present DeepCluster, a clustering method that jointly learns the parameters of a neural network and the cluster assignments of the resulting features.

By: Mathilde Caron, Piotr Bojanowski, Armand Joulin, Matthijs Douze

September 9, 2018

Memory Aware Synapses: Learning what (not) to forget

European Conference on Computer Vision (ECCV)

Humans can learn in a continuous manner. Old rarely utilized knowledge can be overwritten by new incoming information while important, frequently used knowledge is prevented from being erased. In artificial learning systems, lifelong learning so far has focused mainly on accumulating knowledge over tasks and overcoming catastrophic forgetting. In this paper, we argue that, given the limited model capacity and the unlimited new information to be learned, knowledge has to be preserved or erased selectively.

By: Rahaf Aljundi, Francesca Babiloni, Mohamed Elhoseiny, Marcus Rohrbach, Tinne Tuytelaars

September 9, 2018

Choose Your Neuron: Incorporating Domain Knowledge through Neuron-Importance

European Conference on Computer Vision (ECCV)

Individual neurons in convolutional neural networks supervised for image-level classification tasks have been shown to implicitly learn semantically meaningful concepts ranging from simple textures and shapes to whole or partial objects – forming a “dictionary” of concepts acquired through the learning process. In this work we introduce a simple, efficient zero-shot learning approach based on this observation.

By: Ramprasaath R. Selvaraju, Prithvijit Chattopadhyay, Mohamed Elhoseiny, Tilak Sharma, Dhruv Batra, Devi Parikh, Stefan Lee

September 8, 2018

DeepWrinkles: Accurate and Realistic Clothing Modeling

European Conference on Computer Vision (ECCV)

We present a novel method to generate accurate and realistic clothing deformation from real data capture. Previous methods for realistic cloth modeling mainly rely on intensive computation of physics-based simulation (with numerous heuristic parameters), while models reconstructed from visual observations typically suffer from lack of geometric details.

By: Zorah Lähner, Daniel Cremers, Tony Tung

September 7, 2018

Joint Future Semantic and Instance Segmentation Prediction

ECCV Anticipating Human Behavior Workshop

In this work, we introduce a novel prediction approach that encodes instance and semantic segmentation information in a single representation based on distance maps.

By: Camille Couprie, Pauline Luc, Jakob Verbeek

September 7, 2018

Recycle-GAN: Unsupervised Video Retargeting

European Conference on Computer Vision (ECCV)

We introduce a data-driven approach for unsupervised video retargeting that translates content from one domain to another while preserving the style native to a domain, i.e., if contents of John Oliver’s speech were to be transferred to Stephen Colbert, then the generated content/speech should be in Stephen Colbert’s style.

By: Aayush Bansal, Shugao Ma, Deva Ramanan, Yaser Sheikh