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06/15/2023
Encyclopedic VQA: Visual questions about detailed properties of fine-grained categories
We propose Encyclopedic-VQA, a large scale visual question answering (VQ...
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05/17/2023
Infinite Class Mixup
Mixup is a widely adopted strategy for training deep networks, where add...
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06/09/2022
The Missing Link: Finding label relations across datasets
Computer Vision is driven by the many datasets which can be used for tra...
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04/04/2022
How stable are Transferability Metrics evaluations?
Transferability metrics is a maturing field with increasing interest, wh...
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11/25/2021
Transferability Metrics for Selecting Source Model Ensembles
We address the problem of ensemble selection in transfer learning: Given...
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11/24/2021
Transferability Estimation using Bhattacharyya Class Separability
Transfer learning has become a popular method for leveraging pre-trained...
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03/24/2021
Factors of Influence for Transfer Learning across Diverse Appearance Domains and Task Types
Transfer learning enables to re-use knowledge learned on a source task t...
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11/09/2020
EDEN: Multimodal Synthetic Dataset of Enclosed GarDEN Scenes
Multimodal large-scale datasets for outdoor scenes are mostly designed f...
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09/17/2020
Novel View Synthesis from Single Images via Point Cloud Transformation
In this paper the argument is made that for true novel view synthesis of...
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09/03/2020
Multi-Loss Weighting with Coefficient of Variations
Many interesting tasks in machine learning and computer vision are learn...
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08/14/2020
PointMixup: Augmentation for Point Clouds
This paper introduces data augmentation for point clouds by interpolatio...
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06/23/2020
Post-hoc Calibration of Neural Networks
Calibration of neural networks is a critical aspect to consider when inc...
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06/23/2020
Calibration of Neural Networks using Splines
Calibrating neural networks is of utmost importance when employing them ...
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05/20/2020
Range Conditioned Dilated Convolutions for Scale Invariant 3D Object Detection
This paper presents a novel 3D object detection framework that processes...
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10/29/2019
On the Benefit of Adversarial Training for Monocular Depth Estimation
In this paper we address the benefit of adding adversarial training to t...
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10/03/2019
3D Neighborhood Convolution: Learning Depth-Aware Features for RGB-D and RGB Semantic Segmentation
A key challenge for RGB-D segmentation is how to effectively incorporate...
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12/05/2018
Unsupervised Generation of Optical Flow Datasets from Videos in the Wild
Dense optical flow ground truth of non-rigid motion for real-world image...
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07/19/2018
Three for one and one for three: Flow, Segmentation, and Surface Normals
Optical flow, semantic segmentation, and surface normals represent diffe...
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04/16/2018
IterGANs: Iterative GANs to Learn and Control 3D Object Transformation
We are interested in learning visual representations which allow for 3D ...
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01/30/2018
The New Modality: Emoji Challenges in Prediction, Anticipation, and Retrieval
Over the past decade, emoji have emerged as a new and widespread form of...
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04/08/2016
Online Open World Recognition
As we enter into the big data age and an avalanche of images have become...
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10/06/2015
