21-3 ICLR seminars: Talk 1: Skip RNN: Learning to Skip State Updates in Recurrent Neural Networks, by Victor Campos, Talk 2: Graph Attention Networks, by Guillem Cucurull
18-10 Presentation from Marco Buzzelli on his thesis research sofar.
11-10 Xialei on learning without forgetting
6-10 Marc on New Pattern Discovery
26-9 CVPR/ICCV meeting:
Focal Loss for Dense Object Detection, ICCV 2017 (Javad)
Top-down Visual Saliency Guided by Captions, CVPR 2017 (Carola)
20-9 CVPR/ICCV meeting:
Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization ,ICCV2017 (Yaxing)
Adversarial Discriminative Domain Adaptation, CVPR 2017 (Oğuz)
15-9 CVPR/ICCV meeting:
Incremental Learning of Object Detectors without Catastrophic Forgetting, ICCV2017, (Xialei)
FC4: Fully Convolutional Color Constancy With Confidence-Weighted Pooling, CVPR 2017 (Rada)
15-9 Jan van Gemert is visiting and gives a seminar on ‘Active Decision Boundary Annotation with Deep Generative Models’
6-9 CVPR/ICCV meeting: CREST: Convolutional Residual Learning for Visual Tracking.(Lichao) Attend in groups: a weakly-supervised deep learning framework for learning from web data.(Lu) On Compressing Deep Models by Low Rank and Sparse Decomposition (Marc)
18-5 We will discuss the paper BEGAN: Boundary Equilibrium Generative Adversarial Networks
Marc presents his work
11-5 Yaxing presents his work on ‘Multiresolution GANs’
28-4 ICLR meeting3 (short presentations): LEARNING PRUNING FILTERS FOR EFFICIENT CONVNETS LEARNING TO REMEMBER RARE EVENTS
20-4 ICLR meeting2 (short presentations): DEEP PREDICTIVE CODING NETWORKS FOR VIDEO PREDICTION AND UNSUPERVISED LEARNING PRUNING FILTERS FOR EFFICIENT CONVNETS LEARNING TO REMEMBER RARE EVENTS ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation REINFORCEMENT LEARNING AUXILIARY TASKS Highway and Residual Networks learn Unrolled Iterative Estimation
18-4 We have a talk from Damien Muselet ‘Towards an Electronic Orientation Table: Using Features Extracted From the Image to Register Digital Elevation Model’
6-4 ICLR meeting (short presentations): Understanding deep learning requires rethinking generalization Learning Features of Music from Scratch Understanding intermediate layers using linear classifier probes Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Transfer Optimization as a model for few shot learning
11-12** NIPS 2016 short presentations:** Residual Networks Behave Like Ensembles of Relatively Shallow Networks Training and Evaluating Multimodal Word Embeddings with Large-scale Web Annotated Images Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling Learning feed-forward one-shot learners Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks Domain Separation Networks Coupled Generative Adversarial Networks Learning the Number of Neurons in Deep Networks Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks SoundNet: Learning Sound Representations from Unlabeled Video
29-11 NIPS 2016 short presentations: Learning What and Where to Draw R-FCN: Object Detection via Region-based Fully Convolutional Networks Single-Image Depth Perception in the Wild PerforatedCNNs: Acceleration through Elimination of Redundant Convolutions CliqueCNN: Deep Unsupervised Exemplar Learning Learning to learn by gradient descent by gradient descent Conditional Image Generation with PixelCNN Decoders Improved Techniques for Training GANs
2-5 Mikhail
25-4 Oguz
18-4 Carola
5-4 Yaxing presented his submission to ECCV.
21-3 ICLR seminars: Talk 1: Skip RNN: Learning to Skip State Updates in Recurrent Neural Networks, by Victor Campos, Talk 2: Graph Attention Networks, by Guillem Cucurull
7-3 Xialei presents Learning to Segment Every Thing
21-2 Marc presents BIER – Boosting Independent Embeddings Robustly
14-2 Lichao presents DEEP MULTI-SCALE VIDEO PREDICTION BEYOND MEAN SQUARE ERROR
7-2 Javad presents Apprentice: Using Knowledge Distillation Techniques To Improve Low-Precision Network Accuracy
31-1 Bogdan presents Photographic Image Synthesis with Cascaded Refinement Networks
25-1 Aitor presents ‘Learning to Synthesize a 4D RGBD Light Field from a Single Image‘ (ICCV)
17-1 Abel represents his work and we will discuss: Unsupervised Creation of Parameterized Avatars
12-1 Jan van Gemert presents a seminar.
2018
20-12 Luis will present ‘progressive growing of GANs’
15-12 Abel will present: Interpretable and Globally Optimal Prediction for Textual Grounding using Image Concepts
and Lu will present: Memory-Augmented Attribute Manipulation Networks for Interactive Fashion Search
5-12 Fei will present Optical Flow with Semantic Segmentation and Localized Layers
30-11 Chenshen presents NIPS 2017: ‘Continual Learning with Deep Generative Replay’
and Kai will be present ACM-MM ‘Fluency-Guided Cross-Lingual Image Captioning’
24-11 Xialei and Yaxing present their work.
7-11 Deeper, Broader and Artier Domain Generalization
18-10 Presentation from Marco Buzzelli on his thesis research sofar.
11-10 Xialei on learning without forgetting
6-10 Marc on New Pattern Discovery
26-9 CVPR/ICCV meeting:
Focal Loss for Dense Object Detection, ICCV 2017 (Javad)
Top-down Visual Saliency Guided by Captions, CVPR 2017 (Carola)
20-9 CVPR/ICCV meeting:
Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization ,ICCV2017 (Yaxing)
Adversarial Discriminative Domain Adaptation, CVPR 2017 (Oğuz)
15-9 CVPR/ICCV meeting:
Incremental Learning of Object Detectors without Catastrophic Forgetting, ICCV2017, (Xialei)
FC4: Fully Convolutional Color Constancy With Confidence-Weighted Pooling, CVPR 2017 (Rada)
15-9 Jan van Gemert is visiting and gives a seminar on ‘Active Decision Boundary Annotation with Deep Generative Models’
6-9 CVPR/ICCV meeting: CREST: Convolutional Residual Learning for Visual Tracking.(Lichao) Attend in groups: a weakly-supervised deep learning framework for learning from web data.(Lu) On Compressing Deep Models by Low Rank and Sparse Decomposition (Marc)
1-9 Abel Gonzalez presents his thesis work.
31-8 We will discuss the paper ‘YOLO9000: Better, Faster, Stronger’
22-7 Oguz presents his work
17-7 The CVC CVPR reading group.
10-7 We discuss the paper Learning Aligned Cross-Modal Representations from Weakly Aligned Data
29-6 Carola presents her work
22-6 Lichao presents his work, and we will discuss the paper ‘Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks’
8-6 Rada and Lu presents their work
25-5 Xialei presents his work
18-5 We will discuss the paper BEGAN: Boundary Equilibrium Generative Adversarial Networks
Marc presents his work
11-5 Yaxing presents his work on ‘Multiresolution GANs’
28-4 ICLR meeting3 (short presentations):
LEARNING PRUNING FILTERS FOR EFFICIENT CONVNETS
LEARNING TO REMEMBER RARE EVENTS
20-4 ICLR meeting2 (short presentations):
DEEP PREDICTIVE CODING NETWORKS FOR VIDEO PREDICTION AND UNSUPERVISED
LEARNING PRUNING FILTERS FOR EFFICIENT CONVNETS
LEARNING TO REMEMBER RARE EVENTS
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
REINFORCEMENT LEARNING AUXILIARY TASKS
Highway and Residual Networks learn Unrolled Iterative Estimation
18-4 We have a talk from Damien Muselet ‘Towards an Electronic Orientation Table: Using Features Extracted From the Image to Register Digital Elevation Model’
6-4 ICLR meeting (short presentations):
Understanding deep learning requires rethinking generalization
Learning Features of Music from Scratch
Understanding intermediate layers using linear classifier probes
Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Transfer
Optimization as a model for few shot learning
31-3 Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding Akira Fukui, Dong Huk Park, Daylen Yang, Anna Rohrbach, Trevor Darrell, Marcus Rohrbach
We also have a presentation of Marc Bolanos (UB).
24-3 Mask R-CNN Kaiming He, Georgia Gkioxari, Piotr Dollár, Ross Girshick
16-3 Perceptual Losses for Real-Time Style Transfer and Super-Resolution
Justin Johnson, Alexandre Alahi, Li Fei-Fei
9-3 PixelNet: Representation of the pixels, by the pixels, and for the pixels. Aayush Bansal, Xinlei Chen, Bryan Russell, Abhinav Gupta, Deva Ramanan
2-3 Presentation Juntung Pan (UPC) SalGAN: Visual Saliency Prediction with Generative Adversarial Networks
2-3 Unsupervised Pixel–Level Domain Adaptation with Generative Adversarial Networks Bousmalis, K., Silberman, N., Dohan, D., Erhan, D. and Krishnan, D.,
22-2 Recurrent Models of Visual Attention Volodymyr Mnih, Nicolas Heess, Alex Graves, Koray Kavukcuoglu
15-2 Instance-aware Semantic Segmentation via Multi-task Network Cascades Jifeng Dai Kaiming He Jian Sun
8-2 Highway Networks Rupesh Kumar Srivastava, Klaus Greff, Jurgen Schmidhuber
FractalNet: Ultra-Deep Neural Networks without Residuals Gustav Larsson, Michael Maire, Gregory Shakhnarovich
Densely Connected Convolutional Networks Gao Huang, Zhuang Liu, Kilian Q. Weinberger, Laurens van der Maaten
1-2 Unsupervised Domain Adaptation by Backpropagation, Yaroslav Ganin, Victor Lempitsky
25-1 Generating Videos with Scene Dynamics Carl Vondrick, Hamed Pirsiavash, Antonio Torralba
18-1 Generative Image Modeling using Style and Structure Adversarial Networks Xiaolong Wang, Abhinav Gupta
2017
11-12** NIPS 2016 short presentations:**
Residual Networks Behave Like Ensembles of Relatively Shallow Networks
Training and Evaluating Multimodal Word Embeddings with Large-scale Web Annotated Images
Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling
Learning feed-forward one-shot learners
Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks
Domain Separation Networks
Coupled Generative Adversarial Networks
Learning the Number of Neurons in Deep Networks
Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks
SoundNet: Learning Sound Representations from Unlabeled Video
29-11 NIPS 2016 short presentations:
Learning What and Where to Draw
R-FCN: Object Detection via Region-based Fully Convolutional Networks
Single-Image Depth Perception in the Wild
PerforatedCNNs: Acceleration through Elimination of Redundant Convolutions
CliqueCNN: Deep Unsupervised Exemplar Learning
Learning to learn by gradient descent by gradient descent
Conditional Image Generation with PixelCNN Decoders
Improved Techniques for Training GANs
23-11 Learning without Forgetting Zhizhong Li, Derek Hoiem
10-11 You only look once: Unified, real-time object detection Redmon, J., Divvala, S., Girshick, R. and Farhadi, A.,
SSD: Single shot multibox detector Liu, W., Anguelov, D., Erhan, D., Szegedy, C., Reed, S., Fu, C.Y. and Berg, A.C.
3-11 XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks Mohammad Rastegari, Vicente Ordonez, Joseph Redmon, Ali Farhadi
20-10 Learning local feature descriptors with triplets and shallow convolutional neural networks Vassileios Balntas, Edgar Riba, Daniel Ponsa and Krystian Mikolajczyk
6-10 Social LSTM: Human Trajectory Prediction in Crowded Spaces, A. Alahi, K. Goel, V. Ramanathan, A. Robicquet, L. Fei-Fei, S. Savarese
28-9 LSTM introduction (for example here).
21-9 Show and tell: A neural image caption generator Oriol Vinyals, Alexander Toshev, Samy Bengio, Dumitru Erhan
Sequence to Sequence Learning with Neural Networks Ilya Sutskever, Oriol Vinyals, Quoc V. Le
8-9 DenseCap: Fully Convolutional Localization Networks for Dense Captioning Justin Johnson, Andrej Karpathy, Li Fei-Fei
27-7 Fully-Convolutional Siamese Networks for Object Tracking Luca Bertinetto, Jack Valmadre, Joao F. Henriques, Andrea Vedaldi, Philip H. S. Torr
20-7 Generative adversarial text to image synthesis. Reed, Scott, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, and Honglak Lee.
13-7 Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun
2016