Papers › CTAP: Complementary Temporal Action Proposal Generation

CTAP: Complementary Temporal Action Proposal Generation

12 Jul 2018ECCV 2018 9arXiv:1807.04821archive 2025-07-28

Jiyang Gao, Kan Chen, Ram Nevatia

Temporal action proposal generation is an important task, akin to object proposals, temporal action proposals are intended to capture "clips" or temporal intervals in videos that are likely to contain an action. Previous methods can be divided to two groups: sliding window ranking and actionness score grouping. Sliding windows uniformly cover all segments in videos, but the temporal boundaries are imprecise; grouping based method may have more precise boundaries but it may omit some proposals when the quality of actionness score is low. Based on the complementary characteristics of these two methods, we propose a novel Complementary Temporal Action Proposal (CTAP) generator. Specifically, we apply a Proposal-level Actionness Trustworthiness Estimator (PATE) on the sliding windows proposals to generate the probabilities indicating whether the actions can be correctly detected by actionness scores, the windows with high scores are collected. The collected sliding windows and actionness proposals are then processed by a temporal convolutional neural network for proposal ranking and boundary adjustment. CTAP outperforms state-of-the-art methods on average recall (AR) by a large margin on THUMOS-14 and ActivityNet 1.3 datasets. We further apply CTAP as a proposal generation method in an existing action detector, and show consistent significant improvements.

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compute_prob_dist jiyanggao/CTAP/PATE/test_results/post_processing.py official repository unverified MIT (permissive) · 0ea2d9908d139760 · report
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Tasks

Temporal Action Proposal Generation

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Temporal Action Proposal Generation ActivityNet-1.3 CTAP AR@100 73.17 #10 of 11 Archive leaderboard report
Temporal Action Proposal Generation ActivityNet-1.3 CTAP AUC (val) 65.72 #10 of 11 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

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