Search Results for author:
Found 3 papers, 2 papers with code
MiniROAD: Minimal RNN Framework for Online Action Detection
Online Action Detection (OAD) is the task of identifying actions in streaming videos without access to future frames.
Ranked #1 on
Online Action Detection
on TVSeries
DATa: Domain Adaptation-Aided Deep Table Detection Using Visual-Lexical Representations
More specifically, after pre-training one of state-of-the-art vision-based models as our backbone network, we re-train our augmented model, consisting of the vision-based model and the multilayer perceptron (MLP) architecture.
Soft-Landing Strategy for Alleviating the Task Discrepancy Problem in Temporal Action Localization Tasks
Temporal Action Localization (TAL) methods typically operate on top of feature sequences from a frozen snippet encoder that is pretrained with the Trimmed Action Classification (TAC) tasks, resulting in a task discrepancy problem.
