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Found 11 papers, 6 papers with code
AI Competitions and Benchmarks: Dataset Development
Initially, we develop the tasks involved in dataset development and offer insights into their effective management (including requirements, design, implementation, evaluation, distribution, and maintenance).
T-DEED: Temporal-Discriminability Enhancer Encoder-Decoder for Precise Event Spotting in Sports Videos
In this paper, we introduce T-DEED, a Temporal-Discriminability Enhancer Encoder-Decoder for Precise Event Spotting in sports videos.
ASTRA: An Action Spotting TRAnsformer for Soccer Videos
In this paper, we introduce ASTRA, a Transformer-based model designed for the task of Action Spotting in soccer matches.
SADA: Semantic adversarial unsupervised domain adaptation for Temporal Action Localization
Temporal Action Localization (TAL) is a complex task that poses relevant challenges, particularly when attempting to generalize on new -- unseen -- domains in real-world applications.
SoccerNet 2023 Challenges Results
More information on the tasks, challenges, and leaderboards are available on https://www. soccer-net. org.
Gloss-free Sign Language Translation: Improving from Visual-Language Pretraining
Many previous methods employ an intermediate representation, i. e., gloss sequences, to facilitate SLT, thus transforming it into a two-stage task of sign language recognition (SLR) followed by sign language translation (SLT).
Ranked #2 on
Gloss-free Sign Language Translation
on PHOENIX14T
Gloss-free Sign Language Translation
Self-Supervised Learning
+3
SoccerNet 2022 Challenges Results
The SoccerNet 2022 challenges were the second annual video understanding challenges organized by the SoccerNet team.
Video Transformers: A Survey
Transformer models have shown great success handling long-range interactions, making them a promising tool for modeling video.
Dyadformer: A Multi-modal Transformer for Long-Range Modeling of Dyadic Interactions
Personality computing has become an emerging topic in computer vision, due to the wide range of applications it can be used for.
Deep learning with self-supervision and uncertainty regularization to count fish in underwater images
From experiments on both contrasting datasets, we demonstrate our network outperforms the few other deep learning models implemented for solving this task.
Context-Aware Personality Inference in Dyadic Scenarios: Introducing the UDIVA Dataset
This paper introduces UDIVA, a new non-acted dataset of face-to-face dyadic interactions, where interlocutors perform competitive and collaborative tasks with different behavior elicitation and cognitive workload.
