no code implementations • 31 Jan 2024 • Shreyank N Gowda, Yash Thakre, Shashank Narayana Gowda, Xiaobo Jin
This paper offers a comprehensive analysis of recent advancements in video inpainting techniques, a critical subset of computer vision and artificial intelligence.
no code implementations • 21 Jan 2024 • Kiyoon Kim, Shreyank N Gowda, Panagiotis Eustratiadis, Antreas Antoniou, Robert B Fisher
More precisely, we created dataset splits of HMDB-51 or UCF-101 for training, and Kinetics-400 for testing, using the subset of the classes that are overlapping in both train and test datasets.
no code implementations • 10 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.
1 code implementation • 29 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.
no code implementations • 4 Sep 2023 • Chong Zhang, Mingyu Jin, Qinkai Yu, Haochen Xue, Shreyank N Gowda, Xiaobo Jin
Generalized zero-shot learning (GZSL) aims to recognize samples from both seen and unseen classes using only seen class samples for training.
no code implementations • 30 Aug 2023 • Shreyank N Gowda, Dheeraj Pandey, Shashank Narayana Gowda
This paper presents a comprehensive survey of state-of-the-art methods for talking head generation.
no code implementations • 7 Jun 2023 • Shreyank N Gowda, Anurag Arnab, Jonathan Huang
In this paper, we address the challenges posed by the substantial training time and memory consumption associated with video transformers, focusing on the ViViT (Video Vision Transformer) model, in particular the Factorised Encoder version, as our baseline for action recognition tasks.
no code implementations • 6 Apr 2023 • Shreyank N Gowda
Generalized Zero-Shot Learning (GZSL) has emerged as a pivotal research domain in computer vision, owing to its capability to recognize objects that have not been seen during training.
Ranked #1 on Generalized Zero-Shot Learning on CUB-200-2011
no code implementations • 30 Sep 2022 • Anil Batra, Shreyank N Gowda, Frank Keller, Laura Sevilla-Lara
We refer to this task as Procedure Segmentation and Summarization (PSS).
no code implementations • 9 Jun 2022 • Shreyank N Gowda, Marcus Rohrbach, Frank Keller, Laura Sevilla-Lara
We propose to learn what makes a good video for action recognition and select only high-quality samples for augmentation.
Ranked #2 on Few Shot Action Recognition on HMDB51
1 code implementation • 25 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.
1 code implementation • 27 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.
no code implementations • 18 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.
Ranked #2 on Zero-Shot Action Recognition on Olympics
no code implementations • 19 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.
Ranked #4 on Action Recognition on UCF101
1 code implementation • 26 May 2020 • Shreyank N Gowda, Panagiotis Eustratiadis, Timothy Hospedales, Laura Sevilla-Lara
We treat this as a grouping problem by exploiting object proposals and making a joint inference about grouping over both space and time.
no code implementations • 10 Mar 2020 • Shreyank N Gowda, Chun Yuan
Minute pixel changes in an image drastically change the prediction that the deep learning model makes.
no code implementations • 6 Feb 2020 • Shreyank N Gowda, Chun Yuan
Image steganography refers to the process of hiding information inside images.
1 code implementation • 1 Feb 2019 • Shreyank N Gowda, Chun Yuan
These color images are taken as input in the form of RGB images and classification is done without modifying them.
Ranked #4 on Image Classification on SVHN