28 citations · 70 across the 18 of their papers we have counts for
6 papers · 1 filter
High-Fidelity Video Compression based on Invertible Neural Transform and Implicit Conditioning
Siyue Teng, Ho Man Kwan, Yuxuan Jiang +2
Learning-based video compression has recently achieved competitive rate-distortion performance compared to conventional video codecs. However, most existing methods rely on non-inv…
Compressed Video Super-Resolution based on Hierarchical Encoding
Yuxuan Jiang, Siyue Teng, Qiang Zhu +6
This paper presents a general-purpose video super-resolution (VSR) method, dubbed VSR-HE, specifically designed to enhance the perceptual quality of compressed content. Targeting s…
RTSR: A Real-Time Super-Resolution Model for AV1 Compressed Content
Yuxuan Jiang, Jakub Nawała, Chen Feng +4
Super-resolution (SR) is a key technique for improving the visual quality of video content by increasing its spatial resolution while reconstructing fine details. SR has been emplo…
BVI-AOM: A New Training Dataset for Deep Video Compression Optimization
Jakub Nawała, Yuxuan Jiang, Fan Zhang +3
Deep learning is now playing an important role in enhancing the performance of conventional hybrid video codecs. These learning-based methods typically require diverse and represen…
MTKD: Multi-Teacher Knowledge Distillation for Image Super-Resolution
Yuxuan Jiang, Chen Feng, Fan Zhang +1
Knowledge distillation (KD) has emerged as a promising technique in deep learning, typically employed to enhance a compact student network through learning from their high-performa…
Compressing Deep Image Super-resolution Models
Yuxuan Jiang, Jakub Nawala, Fan Zhang +1
Deep learning techniques have been applied in the context of image super-resolution (SR), achieving remarkable advances in terms of reconstruction performance. Existing techniques…