论文标题
探索国家变更捕获异质骨干 @ ego4d手和物体挑战2022 2022
Exploring State Change Capture of Heterogeneous Backbones @ Ego4D Hands and Objects Challenge 2022
论文作者
论文摘要
捕获相互作用对象的状态变化是理解人类对象相互作用的关键技术。该技术报告描述了我们的方法，使用异质性主链进行EGO4D对象状态变化分类和PNR时间定位挑战。在挑战中，我们使用了异质的视频理解骨干，即CSN，带有3D卷积作为操作员，并以变压器为操作员进行视频。我们的方法在OSCC上达到了0.796的精度，同时达到了PNR上的绝对时间定位误差为0.516。这些出色的成绩在EGO4D OSCC和PNR-TL挑战2022的排行榜上排名第一。
Capturing the state changes of interacting objects is a key technology for understanding human-object interactions. This technical report describes our method using heterogeneous backbones for the Ego4D Object State Change Classification and PNR Temporal Localization Challenge. In the challenge, we used the heterogeneous video understanding backbones, namely CSN with 3D convolution as operator and VideoMAE with Transformer as operator. Our method achieves an accuracy of 0.796 on OSCC while achieving an absolute temporal localization error of 0.516 on PNR. These excellent results rank 1st on the leaderboard of Ego4D OSCC & PNR-TL Challenge 2022.
