Search Results for author: Laura Sevilla-Lara

Found 21 papers, 7 papers with code

Efficient Pre-training for Localized Instruction Generation of Videos

no code implementations27 Nov 2023 Anil Batra, Davide Moltisanti, Laura Sevilla-Lara, Marcus Rohrbach, Frank Keller

Understanding such videos is challenging, involving the precise localization of steps and the generation of textual instructions.

Watt For What: Rethinking Deep Learning's Energy-Performance Relationship

no code implementations10 Oct 2023 Shreyank N Gowda, Xinyue Hao, Gen Li, Laura Sevilla-Lara, Shashank Narayana Gowda

Deep learning models have revolutionized various fields, from image recognition to natural language processing, by achieving unprecedented levels of accuracy.

Telling Stories for Common Sense Zero-Shot Action Recognition

1 code implementation29 Sep 2023 Shreyank N Gowda, Laura Sevilla-Lara

The textual narratives forge connections between seen and unseen classes, overcoming the bottleneck of labeled data that has long impeded advancements in this exciting domain.

Action Recognition Common Sense Reasoning +4

LOCATE: Localize and Transfer Object Parts for Weakly Supervised Affordance Grounding

no code implementations CVPR 2023 Gen Li, Varun Jampani, Deqing Sun, Laura Sevilla-Lara

A key step to acquire this skill is to identify what part of the object affords each action, which is called affordance grounding.

Capturing Temporal Information in a Single Frame: Channel Sampling Strategies for Action Recognition

1 code implementation25 Jan 2022 Kiyoon Kim, Shreyank N Gowda, Oisin Mac Aodha, Laura Sevilla-Lara

We address the problem of capturing temporal information for video classification in 2D networks, without increasing their computational cost.

Action Recognition Optical Flow Estimation +2

A New Split for Evaluating True Zero-Shot Action Recognition

1 code implementation27 Jul 2021 Shreyank N Gowda, Laura Sevilla-Lara, Kiyoon Kim, Frank Keller, Marcus Rohrbach

We benchmark several recent approaches on the proposed True Zero-Shot(TruZe) Split for UCF101 and HMDB51, with zero-shot and generalized zero-shot evaluation.

Few-Shot action recognition Few Shot Action Recognition +2

Adaptive Prototype Learning and Allocation for Few-Shot Segmentation

2 code implementations CVPR 2021 Gen Li, Varun Jampani, Laura Sevilla-Lara, Deqing Sun, Jonghyun Kim, Joongkyu Kim

By integrating the SGC and GPA together, we propose the Adaptive Superpixel-guided Network (ASGNet), which is a lightweight model and adapts to object scale and shape variation.

Clustering Few-Shot Semantic Segmentation +1

CLASTER: Clustering with Reinforcement Learning for Zero-Shot Action Recognition

no code implementations18 Jan 2021 Shreyank N Gowda, Laura Sevilla-Lara, Frank Keller, Marcus Rohrbach

Theproblem can be seen as learning a function which general-izes well to instances of unseen classes without losing dis-crimination between classes.

Action Recognition Clustering +4

SMART Frame Selection for Action Recognition

no code implementations19 Dec 2020 Shreyank N Gowda, Marcus Rohrbach, Laura Sevilla-Lara

In this work, however, we focus on the more standard short, trimmed action recognition problem.

Action Recognition

Proceedings of the ICLR Workshop on Computer Vision for Agriculture (CV4A) 2020

no code implementations23 Apr 2020 Yannis Kalantidis, Laura Sevilla-Lara, Ernest Mwebaze, Dina Machuve, Hamed Alemohammad, David Guerena

The workshop was held in conjunction with the International Conference on Learning Representations (ICLR) 2020.

Only Time Can Tell: Discovering Temporal Data for Temporal Modeling

no code implementations19 Jul 2019 Laura Sevilla-Lara, Shengxin Zha, Zhicheng Yan, Vedanuj Goswami, Matt Feiszli, Lorenzo Torresani

However, in current video datasets it has been observed that action classes can often be recognized without any temporal information from a single frame of video.

Benchmarking Motion Estimation +1

FASTER Recurrent Networks for Efficient Video Classification

no code implementations10 Jun 2019 Linchao Zhu, Laura Sevilla-Lara, Du Tran, Matt Feiszli, Yi Yang, Heng Wang

FASTER aims to leverage the redundancy between neighboring clips and reduce the computational cost by learning to aggregate the predictions from models of different complexities.

Action Classification Action Recognition +3

On the Integration of Optical Flow and Action Recognition

no code implementations22 Dec 2017 Laura Sevilla-Lara, Yiyi Liao, Fatma Guney, Varun Jampani, Andreas Geiger, Michael J. Black

Here we take a deeper look at the combination of flow and action recognition, and investigate why optical flow is helpful, what makes a flow method good for action recognition, and how we can make it better.

Action Recognition Optical Flow Estimation +1

Optical Flow in Mostly Rigid Scenes

no code implementations CVPR 2017 Jonas Wulff, Laura Sevilla-Lara, Michael J. Black

Existing algorithms typically focus on either recovering motion and structure under the assumption of a purely static world or optical flow for general unconstrained scenes.

Motion Estimation Optical Flow Estimation

Cannot find the paper you are looking for? You can Submit a new open access paper.