暂无分享,去创建一个
Alexander S. Ecker | Matthias Bethge | Wieland Brendel | Andreas Geiger | Yash Sharma | Marissa A. Weis | Kashyap Chitta | M. Bethge | Wieland Brendel | Andreas Geiger | Y. Sharma | Kashyap Chitta
[1] Alexander Lerchner,et al. COBRA: Data-Efficient Model-Based RL through Unsupervised Object Discovery and Curiosity-Driven Exploration , 2019, ArXiv.
[2] Bin Li,et al. Generative Modeling of Infinite Occluded Objects for Compositional Scene Representation , 2019, ICML.
[3] Andrew Zisserman,et al. Spatial Transformer Networks , 2015, NIPS.
[4] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[5] Jürgen Schmidhuber,et al. Relational Neural Expectation Maximization: Unsupervised Discovery of Objects and their Interactions , 2018, ICLR.
[6] Stefan Roth,et al. MOT16: A Benchmark for Multi-Object Tracking , 2016, ArXiv.
[7] Alexander Lerchner,et al. Spatial Broadcast Decoder: A Simple Architecture for Learning Disentangled Representations in VAEs , 2019, ArXiv.
[8] Sungjin Ahn,et al. SPACE: Unsupervised Object-Oriented Scene Representation via Spatial Attention and Decomposition , 2020, ICLR.
[9] Ingmar Posner,et al. GENESIS: Generative Scene Inference and Sampling with Object-Centric Latent Representations , 2019, ICLR.
[10] Jürgen Schmidhuber,et al. Neural Expectation Maximization , 2017, NIPS.
[11] Yee Whye Teh,et al. Sequential Attend, Infer, Repeat: Generative Modelling of Moving Objects , 2018, NeurIPS.
[12] Alex Graves,et al. Recurrent Models of Visual Attention , 2014, NIPS.
[13] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[14] Matthew Botvinick,et al. MONet: Unsupervised Scene Decomposition and Representation , 2019, ArXiv.
[15] Thomas Brox,et al. U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.
[16] Luca Iocchi,et al. Independent multimodal background subtraction , 2012, CompIMAGE.
[17] Geoffrey E. Hinton,et al. Attend, Infer, Repeat: Fast Scene Understanding with Generative Models , 2016, NIPS.
[18] Harri Valpola,et al. Tagger: Deep Unsupervised Perceptual Grouping , 2016, NIPS.
[19] Joelle Pineau,et al. Spatially Invariant Unsupervised Object Detection with Convolutional Neural Networks , 2019, AAAI.
[20] Eero P. Simoncelli,et al. Perceptual straightening of natural videos , 2019, Nature Neuroscience.
[21] Peter V. Gehler,et al. Towards causal generative scene models via competition of experts , 2020, ArXiv.
[22] Klaus Greff,et al. Multi-Object Representation Learning with Iterative Variational Inference , 2019, ICML.
[23] David Barber,et al. Tracking by Animation: Unsupervised Learning of Multi-Object Attentive Trackers , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[24] Jiajun Wu,et al. Entity Abstraction in Visual Model-Based Reinforcement Learning , 2019, CoRL.
[25] Yisong Yue,et al. Iterative Amortized Inference , 2018, ICML.
[26] Rainer Stiefelhagen,et al. Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics , 2008, EURASIP J. Image Video Process..
[27] Andreas Geiger,et al. MOTS: Multi-Object Tracking and Segmentation , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[28] Ben Poole,et al. Categorical Reparameterization with Gumbel-Softmax , 2016, ICLR.
[29] Max Welling,et al. Auto-Encoding Variational Bayes , 2013, ICLR.
[30] Natalia Gimelshein,et al. PyTorch: An Imperative Style, High-Performance Deep Learning Library , 2019, NeurIPS.
[31] Yoshua Bengio,et al. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation , 2014, EMNLP.