Lightweight Optical Flow Estimation Using 1D Matching
Author:
Affiliation:
1. Korea Advanced Institute of Science and Technology, Daejeon, South Korea
2. Samsung Electronics, Suwon-si, South Korea
Funder
Samsung Electronics
Institute of Information & Communications Technology Planning & Evaluation (IITP) grant
Korean Government [Ministry of Science and Information and Communications Technology (MSIT)]
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/6287639/10380310/10477999.pdf?arnumber=10477999
Reference29 articles.
1. FlowNet: Learning Optical Flow with Convolutional Networks
2. FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
3. PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume
4. Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions
5. RAFT: Recurrent All-Pairs Field Transforms for Optical Flow
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