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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence

Learned Video Compression via Joint Spatial-Temporal Correlation Exploration

February 1, 2023

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Authors

Haojie Liu

Nanjing University


Han Shen

Horizon Robotics


Lichao Huang

Horizon Robotics


Ming Lu

Nanjing University


Tong Chen

Nanjing University


Zhan Ma

Nanjing University


DOI:

10.1609/aaai.v34i07.6825


Abstract:

Traditional video compression technologies have been developed over decades in pursuit of higher coding efficiency. Efficient temporal information representation plays a key role in video coding. Thus, in this paper, we propose to exploit the temporal correlation using both first-order optical flow and second-order flow prediction. We suggest an one-stage learning approach to encapsulate flow as quantized features from consecutive frames which is then entropy coded with adaptive contexts conditioned on joint spatial-temporal priors to exploit second-order correlations. Joint priors are embedded in autoregressive spatial neighbors, co-located hyper elements and temporal neighbors using ConvLSTM recurrently. We evaluate our approach for the low-delay scenario with High-Efficiency Video Coding (H.265/HEVC), H.264/AVC and another learned video compression method, following the common test settings. Our work offers the state-of-the-art performance, with consistent gains across all popular test sequences.

Topics: AAAI

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HOW TO CITE:

Haojie Liu||Han Shen||Lichao Huang||Ming Lu||Tong Chen||Zhan Ma Learned Video Compression via Joint Spatial-Temporal Correlation Exploration Proceedings of the AAAI Conference on Artificial Intelligence (2020) 11580-11587.

Haojie Liu||Han Shen||Lichao Huang||Ming Lu||Tong Chen||Zhan Ma Learned Video Compression via Joint Spatial-Temporal Correlation Exploration AAAI 2020, 11580-11587.

Haojie Liu||Han Shen||Lichao Huang||Ming Lu||Tong Chen||Zhan Ma (2020). Learned Video Compression via Joint Spatial-Temporal Correlation Exploration. Proceedings of the AAAI Conference on Artificial Intelligence, 11580-11587.

Haojie Liu||Han Shen||Lichao Huang||Ming Lu||Tong Chen||Zhan Ma. Learned Video Compression via Joint Spatial-Temporal Correlation Exploration. Proceedings of the AAAI Conference on Artificial Intelligence 2020 p.11580-11587.

Haojie Liu||Han Shen||Lichao Huang||Ming Lu||Tong Chen||Zhan Ma. 2020. Learned Video Compression via Joint Spatial-Temporal Correlation Exploration. "Proceedings of the AAAI Conference on Artificial Intelligence". 11580-11587.

Haojie Liu||Han Shen||Lichao Huang||Ming Lu||Tong Chen||Zhan Ma. (2020) "Learned Video Compression via Joint Spatial-Temporal Correlation Exploration", Proceedings of the AAAI Conference on Artificial Intelligence, p.11580-11587

Haojie Liu||Han Shen||Lichao Huang||Ming Lu||Tong Chen||Zhan Ma, "Learned Video Compression via Joint Spatial-Temporal Correlation Exploration", AAAI, p.11580-11587, 2020.

Haojie Liu||Han Shen||Lichao Huang||Ming Lu||Tong Chen||Zhan Ma. "Learned Video Compression via Joint Spatial-Temporal Correlation Exploration". Proceedings of the AAAI Conference on Artificial Intelligence, 2020, p.11580-11587.

Haojie Liu||Han Shen||Lichao Huang||Ming Lu||Tong Chen||Zhan Ma. "Learned Video Compression via Joint Spatial-Temporal Correlation Exploration". Proceedings of the AAAI Conference on Artificial Intelligence, (2020): 11580-11587.

Haojie Liu||Han Shen||Lichao Huang||Ming Lu||Tong Chen||Zhan Ma. Learned Video Compression via Joint Spatial-Temporal Correlation Exploration. AAAI[Internet]. 2020[cited 2023]; 11580-11587.


ISSN: 2374-3468


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