Action Anticipation
34 papers with code • 6 benchmarks • 8 datasets
Next action anticipation is defined as observing 1, ... , T frames and predicting the action that happens after a gap of T_a seconds. It is important to note that a new action starts after T_a seconds that is not seen in the observed frames. Here T_a=1 second.
Benchmarks
These leaderboards are used to track progress in Action Anticipation
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
EPIC-KITCHENS-100
EGTEA
Assembly101
TVSeries
Ego4D
CP2A dataset
Most implemented papers
Rescaling Egocentric Vision
This paper introduces the pipeline to extend the largest dataset in egocentric vision, EPIC-KITCHENS.
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.
What Would You Expect? Anticipating Egocentric Actions with Rolling-Unrolling LSTMs and Modality Attention
fpv-iplab/rulstm
•
•
ICCV 2019
Our method is ranked first in the public leaderboard of the EPIC-Kitchens egocentric action anticipation challenge 2019.
HalluciNet-ing Spatiotemporal Representations Using a 2D-CNN
The hallucination task is treated as an auxiliary task, which can be used with any other action related task in a multitask learning setting.
Rolling-Unrolling LSTMs for Action Anticipation from First-Person Video
fpv-iplab/rulstm
•
•
The experiments show that the proposed architecture is state-of-the-art in the domain of egocentric videos, achieving top performances in the 2019 EPIC-Kitchens egocentric action anticipation challenge.
Temporal Aggregate Representations for Long-Range Video Understanding
dibschat/tempAgg
•
•
ECCV 2020
Future prediction, especially in long-range videos, requires reasoning from current and past observations.
Encouraging LSTMs to Anticipate Actions Very Early
In contrast to the widely studied problem of recognizing an action given a complete sequence, action anticipation aims to identify the action from only partially available videos.
RED: Reinforced Encoder-Decoder Networks for Action Anticipation
RED takes multiple history representations as input and learns to anticipate a sequence of future representations.
Forecasting Human-Object Interaction: Joint Prediction of Motor Attention and Actions in First Person Video
2020aptx4869lm/Forecasting-Human-Object-Interaction-in-FPV
•
•
ECCV 2020
Motivated by this, we adopt intentional hand movement as a future representation and propose a novel deep network that jointly models and predicts the egocentric hand motion, interaction hotspots and future action.
Pedestrian Action Anticipation using Contextual Feature Fusion in Stacked RNNs
aras62/SF-GRU
•
•
To this end, we propose a solution for the problem of pedestrian action anticipation at the point of crossing.
