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Found 5 papers, 2 papers with code
Few-Shot Classification of Interactive Activities of Daily Living (InteractADL)
Understanding Activities of Daily Living (ADLs) is a crucial step for different applications including assistive robots, smart homes, and healthcare.
Ranked #1 on
Few Shot Action Recognition
on MOMA-LRG
(using extra training data)
Few Shot Action Recognition
Fine-Grained Image Classification
+2
Agile Modeling: From Concept to Classifier in Minutes
In reaction, we introduce the problem of Agile Modeling: the process of turning any subjective visual concept into a computer vision model through a real-time user-in-the-loop interactions.
JRDB-Pose: A Large-scale Dataset for Multi-Person Pose Estimation and Tracking
In crowded human scenes with close-up human-robot interaction and robot navigation, a deep understanding requires reasoning about human motion and body dynamics over time with human body pose estimation and tracking.
SoMoFormer: Multi-Person Pose Forecasting with Transformers
Although there are several previous works targeting the problem of multi-person dynamic pose forecasting, they often model the entire pose sequence as time series (ignoring the underlying relationship between joints) or only output the future pose sequence of one person at a time.
Understanding Transfer Learning for Chest Radiograph Clinical Report Generation with Modified Transformer Architectures
In this paper we demonstrate the importance of domain specific pre-training and propose a modified transformer architecture for the medical image captioning task.
