b'Hilde Kuehne'

research

∙ 09/16/2023

In-Style: Bridging Text and Uncurated Videos with Style Transfer for Text-Video Retrieval

Large-scale noisy web image-text datasets have been proven to be efficie...

0 Nina Shvetsova, et al. ∙

research

∙ 08/24/2023

Preserving Modality Structure Improves Multi-Modal Learning

Self-supervised learning on large-scale multi-modal datasets allows lear...

0 Swetha Sirnam, et al. ∙

research

∙ 05/21/2023

Comparison of Multilingual Self-Supervised and Weakly-Supervised Speech Pre-Training for Adaptation to Unseen Languages

Recent models such as XLS-R and Whisper have made multilingual speech te...

0 Andrew Rouditchenko, et al. ∙

research

∙ 05/01/2023

ISAAC Newton: Input-based Approximate Curvature for Newton's Method

We present ISAAC (Input-baSed ApproximAte Curvature), a novel method tha...

0 Felix Petersen, et al. ∙

research

∙ 04/11/2023

WEAR: A Multimodal Dataset for Wearable and Egocentric Video Activity Recognition

Though research has shown the complementarity of camera- and inertial-ba...

0 Marius Bock, et al. ∙

research

∙ 03/29/2023

What, when, and where? – Self-Supervised Spatio-Temporal Grounding in Untrimmed Multi-Action Videos from Narrated Instructions

Spatio-temporal grounding describes the task of localizing events in spa...

0 Brian Chen, et al. ∙

research

∙ 03/23/2023

Temperature Schedules for Self-Supervised Contrastive Methods on Long-Tail Data

Most approaches for self-supervised learning (SSL) are optimised on cura...

0 Anna Kukleva, et al. ∙

research

∙ 03/15/2023

MAtch, eXpand and Improve: Unsupervised Finetuning for Zero-Shot Action Recognition with Language Knowledge

Large scale Vision-Language (VL) models have shown tremendous success in...

0 Wei Lin, et al. ∙

research

∙ 03/09/2023

TAEC: Unsupervised Action Segmentation with Temporal-Aware Embedding and Clustering

Temporal action segmentation in untrimmed videos has gained increased at...

0 Wei Lin, et al. ∙

research

∙ 01/05/2023

Learning by Sorting: Self-supervised Learning with Group Ordering Constraints

Contrastive learning has become a prominent ingredient in learning repre...

0 Nina Shvetsova, et al. ∙

research

∙ 11/24/2022

Video Test-Time Adaptation for Action Recognition

Although action recognition systems can achieve top performance when eva...

0 Wei Lin, et al. ∙

research

∙ 10/15/2022

Deep Differentiable Logic Gate Networks

Recently, research has increasingly focused on developing efficient neur...

0 Felix Petersen, et al. ∙

research

∙ 10/07/2022

C2KD: Cross-Lingual Cross-Modal Knowledge Distillation for Multilingual Text-Video Retrieval

Multilingual text-video retrieval methods have improved significantly in...

0 Andrew Rouditchenko, et al. ∙

research

∙ 09/12/2022

VL-Taboo: An Analysis of Attribute-based Zero-shot Capabilities of Vision-Language Models

Vision-language models trained on large, randomly collected data had sig...

0 Felix Vogel, et al. ∙

research

∙ 08/03/2022

Augmentation Learning for Semi-Supervised Classification

Recently, a number of new Semi-Supervised Learning methods have emerged....

0 Tim Frommknecht, et al. ∙

research

∙ 07/05/2022

Weakly Supervised Grounding for VQA in Vision-Language Transformers

Transformers for visual-language representation learning have been getti...

0 Aisha Urooj Khan, et al. ∙

research

∙ 06/15/2022

Differentiable Top-k Classification Learning

The top-k classification accuracy is one of the core metrics in machine ...

0 Felix Petersen, et al. ∙

research

∙ 03/30/2022

CycDA: Unsupervised Cycle Domain Adaptation from Image to Video

Although action recognition has achieved impressive results over recent ...

5 Wei Lin, et al. ∙

research

∙ 03/17/2022

Monotonic Differentiable Sorting Networks

Differentiable sorting algorithms allow training with sorting and rankin...

1 Felix Petersen, et al. ∙

research

∙ 12/08/2021

Everything at Once – Multi-modal Fusion Transformer for Video Retrieval

Multi-modal learning from video data has seen increased attention recent...

0 Nina Shvetsova, et al. ∙

research

∙ 12/04/2021

Unsupervised Domain Generalization by Learning a Bridge Across Domains

The ability to generalize learned representations across significantly d...

6 Sivan Harary, et al. ∙

research

∙ 12/01/2021

Routing with Self-Attention for Multimodal Capsule Networks

The task of multimodal learning has seen a growing interest recently as ...

0 Kevin Duarte, et al. ∙

research

∙ 11/08/2021

Cascaded Multilingual Audio-Visual Learning from Videos

In this paper, we explore self-supervised audio-visual models that learn...

0 Andrew Rouditchenko, et al. ∙

research

∙ 10/20/2021

Style Agnostic 3D Reconstruction via Adversarial Style Transfer

Reconstructing the 3D geometry of an object from an image is a major cha...

0 Felix Petersen, et al. ∙

research

∙ 10/11/2021

Learning with Algorithmic Supervision via Continuous Relaxations

The integration of algorithmic components into neural architectures has ...

0 Felix Petersen, et al. ∙

research

∙ 08/18/2021

Generalized and Incremental Few-Shot Learning by Explicit Learning and Calibration without Forgetting

Both generalized and incremental few-shot learning have to deal with thr...

0 Anna Kukleva, et al. ∙

research

∙ 05/11/2021

Found a Reason for me? Weakly-supervised Grounded Visual Question Answering using Capsules

The problem of grounding VQA tasks has seen an increased attention in th...

0 Aisha Urooj Khan, et al. ∙

research

∙ 05/09/2021

Differentiable Sorting Networks for Scalable Sorting and Ranking Supervision

Sorting and ranking supervision is a method for training neural networks...

0 Felix Petersen, et al. ∙

research

∙ 04/30/2021

Unsupervised Discriminative Embedding for Sub-Action Learning in Complex Activities

Action recognition and detection in the context of long untrimmed video ...

0 Sirnam Swetha, et al. ∙

research

∙ 04/26/2021

Multimodal Clustering Networks for Self-supervised Learning from Unlabeled Videos

Multimodal self-supervised learning is getting more and more attention a...

0 Brian Chen, et al. ∙

research

∙ 04/20/2021

Detector-Free Weakly Supervised Grounding by Separation

Nowadays, there is an abundance of data involving images and surrounding...

7 Assaf Arbelle, et al. ∙

research

∙ 01/29/2020

Joint Visual-Temporal Embedding for Unsupervised Learning of Actions in Untrimmed Sequences

Understanding the structure of complex activities in videos is one of th...

17 Rosaura G. VidalMata, et al. ∙

research

∙ 12/02/2019

More Is Less: Learning Efficient Video Representations by Big-Little Network and Depthwise Temporal Aggregation

Current state-of-the-art models for video action recognition are mostly ...

5 Quanfu Fan, et al. ∙

research

∙ 06/03/2019

A Hybrid RNN-HMM Approach for Weakly Supervised Temporal Action Segmentation

Action recognition has become a rapidly developing research field within...

0 Hilde Kuehne, et al. ∙

research

∙ 06/03/2019

Mining YouTube - A dataset for learning fine-grained action concepts from webly supervised video data

Action recognition is so far mainly focusing on the problem of classific...

0 Hilde Kuehne, et al. ∙

research

∙ 04/08/2019

Unsupervised learning of action classes with continuous temporal embedding

The task of temporally detecting and segmenting actions in untrimmed vid...

0 Anna Kukleva, et al. ∙

research

∙ 05/17/2018

NeuralNetwork-Viterbi: A Framework for Weakly Supervised Video Learning

Video learning is an important task in computer vision and has experienc...

0 Alexander Richard, et al. ∙

research

∙ 06/27/2017

Recurrent Residual Learning for Action Recognition

Action recognition is a fundamental problem in computer vision with a lo...

0 Ahsan Iqbal, et al. ∙

research

∙ 06/02/2017

Temporal Action Labeling using Action Sets

Action detection and temporal segmentation of actions in videos are topi...

0 Alexander Richard, et al. ∙

research

∙ 03/23/2017

Weakly Supervised Action Learning with RNN based Fine-to-coarse Modeling

We present an approach for weakly supervised learning of human actions. ...

0 Alexander Richard, et al. ∙

research

∙ 10/07/2016

Weakly supervised learning of actions from transcripts

We present an approach for weakly supervised learning of human actions f...

0 Hilde Kuehne, et al. ∙

research

∙ 09/07/2015

An end-to-end generative framework for video segmentation and recognition

We describe an end-to-end generative approach for the segmentation and r...

0 Hilde Kuehne, et al. ∙

Hilde Kuehne

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