FusedLSTM: Fusing frame-level and video-level features for Content-based Video Relevance Prediction

29 Sep 2018 Yash Bhalgat

This paper describes two of my best performing approaches on the Content-based Video Relevance Prediction challenge. In the FusedLSTM based approach, the inception-pool3 and the C3D-pool5 features are combined using an LSTM and a dense layer to form embeddings with the objective to minimize the triplet loss function... (read more)

PDF Abstract
No code implementations yet. Submit your code now


Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper

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