ECO: Efficient Convolutional Network for Online Video Understanding

The state of the art in video understanding suffers from two problems: (1) The major part of reasoning is performed locally in the video, therefore, it misses important relationships within actions that span several seconds. (2) While there are local methods with fast per-frame processing, the processing of the whole video is not efficient and hampers fast video retrieval or online classification of long-term activities... (read more)

PDF Abstract ECCV 2018 PDF ECCV 2018 Abstract

Results from the Paper


Ranked #36 on Action Recognition on Something-Something V1 (using extra training data)

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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK USES EXTRA
TRAINING DATA
BENCHMARK
Action Recognition Something-Something V1 ECO-Net (ImageNet pretrained) Top 1 Accuracy 46.4 # 36

Results from Other Papers


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK USES EXTRA
TRAINING DATA
SOURCE PAPER COMPARE
Action Recognition Something-Something V1 ECO-Net Top 1 Accuracy 46.4 # 36
Action Recognition UCF101 ECO 3-fold Accuracy 93.6 # 49

Methods used in the Paper


METHOD TYPE
🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet