25-5 Profesor Henry Medeiros gives a talk in the group: Applications of Semantic Image Segmentation in Agricultural Automation and Assisted Living Environments
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
Tentative schedule:
June 27: Lu
June 13: Marc
June 6: Mikel presents FearNet: Brain-Inspired Model for Incremental Learning
May 10: Lichao presents Learning Discriminative Model Prediction for Tracking
May 2: Kai presents his work and
Fei presents:
Efficient Variable Rate Image Compression with Multi-scale Decomposition Network, Trans. on CSVT, 2019
Apr 9: Marc and Lu present their own work.
Apr 4: Kai wil present
Hardness-Aware Deep Metric Learning (CVPR2019 oral)
Oguz presents his work.
Mar 28: Lichao will present his work.
Carola will present:
Large Scale Fine-Grained Categorization and Domain-Specific Transfer
Learning
(CVPR 2018)
Mar 7: Chenshen will present:
The lottery ticket hypothesis: finding sparse, trainable neural networks
(ICLR 2019 Oral)
Feb 28: Xialei will present:
On the Sensitivity of Adversarial Robustness to Input Data Distributions (ICLR 2019)
Oguz will present:
Semantic Regularisation for Recurrent Image Annotation
(CVPR2017)
Feb 14: Yaxing will present:
Unsupervised Learning of Object Landmarks through Conditional Image Generation
(NIPS2018)
Javad will present:
Large-Scale Visual Active Learning with Deep Probabilistic Ensembles
(ARXIV2018)
Dec 12 Lichao will present his recent work.
Kai will present Robust Classification with Convolutional Prototype Learning (CVPR2018)
Nov 28 Lu will present the paper: Learning to Compare: Relation Network for Few-Shot Learning.
Yaxing will present his recent research.
Nov 7: Carola will present Associating Inter-image Salient Instances for Weakly Supervised Semantic Segmentation (ECCV 2018)
Bogdan will present Progress & Compress: A scalable framework for continual learning (ICLR 2018)
Oct 31: Chenshen will present Large Scale GAN Training for High Fidelity Natural Image Synthesis
Oct 17: Oguz will present Deep Randomized Ensembles for Metric Learning (ECCV 2018)
Abel will present What do I Annotate Next? An Empirical Study of Active Learning for Action Localization
Oct 10: Marc presents Memory Aware Synapses: Learning what (not) to forget
Sept 19: Fei presents DF-Net: Unsupervised Joint Learning of Depth and Flow using Cross-Task Consistency (ECCV 2018)
Laura presents: Group Normalization (ECCV 2018)
Sept 5:Xialei presents Deep Matching Autoencoders (CVPR 2018)
13- 6 Kai will present Self-supervised learning of visual features through embedding images into text topic spaces (CVPR2017)
Chenshen will present his latest research.
30-5 CVPR Meeting: Lu will present VITON: An Image-based Virtual Try-on Network
Chenshen will present Unsupervised Feature Learning via Non-Parametric Instance Discrimination
Fei will present Context-aware Synthesis for Video Frame Interpolation
Laura will present Look, Imagine and Match: Improving Textual-Visual Cross-Modal Retrieval With Generative Models
25-5 Profesor Henry Medeiros gives a talk in the group: Applications of Semantic Image Segmentation in Agricultural Automation and Assisted Living Environments
23-5 Carola will present: Weakly Supervised Salient Object Detection Using Image Labels
Oguz will present: Learning Attribute Representations With Localization for Flexible Fashion Search
Lichao will present: Fast and Accurate Online Video Object Segmentation via Tracking Parts
11-5 Lu will discuss here submission to BMVC.
2-5 Luis will present ‘FiLM: Visual Reasoning with a General Conditioning Layer’ and Abel will present ‘Multimodal Unsupervised Image-to-Image Translation‘.
18-4 CVC CVPR meeting (Abel, Xialei, Yaxing, Javier)
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