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Found 16 papers, 10 papers with code
Spatial Cognition from Egocentric Video: Out of Sight, Not Out of Mind
As humans move around, performing their daily tasks, they are able to recall where they have positioned objects in their environment, even if these objects are currently out of sight.
Centre Stage: Centricity-based Audio-Visual Temporal Action Detection
Previous one-stage action detection approaches have modelled temporal dependencies using only the visual modality.
What can a cook in Italy teach a mechanic in India? Action Recognition Generalisation Over Scenarios and Locations
We propose and address a new generalisation problem: can a model trained for action recognition successfully classify actions when they are performed within a previously unseen scenario and in a previously unseen location?
Use Your Head: Improving Long-Tail Video Recognition
We demonstrate that, unlike naturally-collected video datasets and existing long-tail image benchmarks, current video benchmarks fall short on multiple long-tailed properties.
Refining Action Boundaries for One-stage Detection
We obtain state-of-the-art performance on the challenging EPIC-KITCHENS-100 action detection as well as the standard THUMOS14 action detection benchmarks, and achieve improvement on the ActivityNet-1. 3 benchmark.
Inertial Hallucinations -- When Wearable Inertial Devices Start Seeing Things
We propose a novel approach to multimodal sensor fusion for Ambient Assisted Living (AAL) which takes advantage of learning using privileged information (LUPI).
An Evaluation of OCR on Egocentric Data
In this paper, we evaluate state-of-the-art OCR methods on Egocentric data.
TVNet: Temporal Voting Network for Action Localization
This incorporates a novel Voting Evidence Module to locate temporal boundaries, more accurately, where temporal contextual evidence is accumulated to predict frame-level probabilities of start and end action boundaries.
Temporal-Relational CrossTransformers for Few-Shot Action Recognition
We propose a novel approach to few-shot action recognition, finding temporally-corresponding frame tuples between the query and videos in the support set.
Meta-Learning with Context-Agnostic Initialisations
This produces an initialisation for fine-tuning to target which is both context-agnostic and task-generalised.
Rescaling Egocentric Vision
This paper introduces the pipeline to extend the largest dataset in egocentric vision, EPIC-KITCHENS.
Ranked #6 on
Action Anticipation
on EPIC-KITCHENS-100
The EPIC-KITCHENS Dataset: Collection, Challenges and Baselines
Our dataset features 55 hours of video consisting of 11. 5M frames, which we densely labelled for a total of 39. 6K action segments and 454. 2K object bounding boxes.
Sit-to-Stand Analysis in the Wild using Silhouettes for Longitudinal Health Monitoring
We present the first fully automated Sit-to-Stand or Stand-to-Sit (StS) analysis framework for long-term monitoring of patients in free-living environments using video silhouettes.
DDLSTM: Dual-Domain LSTM for Cross-Dataset Action Recognition
Domain alignment in convolutional networks aims to learn the degree of layer-specific feature alignment beneficial to the joint learning of source and target datasets.
Scaling Egocentric Vision: The EPIC-KITCHENS Dataset
First-person vision is gaining interest as it offers a unique viewpoint on people's interaction with objects, their attention, and even intention.
Cost-based Feature Transfer for Vehicle Occupant Classification
Knowledge of human presence and interaction in a vehicle is of growing interest to vehicle manufacturers for design and safety purposes.
