Challenge papers

C. Zhug, Y. Chai, T. Jiang, M. Lu, and T. Chen
TinyLIC - high efficiency lossy image compression method
2024
URL, RIS, BibTex

Y. Zhao, W. He, C. Jia, Q. Wang, J. Li, Y. Li, C. Lin, K. Zhang, et al.
A Neural-network Enhanced Video Coding Framework beyond ECM
2024
URL, RIS, BibTex

S. F. Hosseini-Benvidi, H. Motamednia, A. Mansouri, M. Raei, and A. Mahmoudi-Aznaveh
Compressed image quality assessment using stacking
2024
URL, RIS, BibTex

Z. Yu, F. Guan, Y. Lu, X. Li, and Z. Chen
Video Quality Assessment Based on Swin TransformerV2 and Coarse to Fine Strategy
2024
URL, RIS, BibTex

H. Wang, X. Pan, Z. Guo, R. Feng, and Z. Chen
Conditional Neural Video Coding with Spatial-Temporal Super-Resolution
2024
URL, RIS, BibTex

N. Fu, J. Zhang, H. Wang, and Z. Chen
Perceptual-oriented Learned Image Compression with Dynamic Kernel
2024
URL, RIS, BibTex

D. A. Ramsook and A. Kokaram
A Neural Enhancement Post-Processor with a Dynamic AV1 Encoder Configuration Strategy for CLIC 2024
2024
URL, RIS, BibTex

R. Yu, Y. Luo, X. Jiang, T. Jiang, X. Wu, K. Wu, and P. Wei
Progressive Future Fusion Network for Enhancing Image Quality Assessment
2024
URL, RIS, BibTex

J. Zhang, Z. Li, Y. Wang, X. Zeng, Z. Zhang, N. Wang, Y. Long, and M. Jia
A Video Coding Method Based on Neural Network for CLIC2024
2024
URL, RIS, BibTex

J. Yang, W. Jiang, Y. Zhai, C. Yang, and R. Wang
UCVC: A Unified Contextual Video Compression Framework with Joint P-frame and B-frame Coding
2024
URL, RIS, BibTex

D. Li, K. Wang, Y. Bai, X. Liu, and W. Gao
Local Semantic Loss and Latent Refinement for Perception-Oriented Neural Compression
2024
URL, RIS, BibTex

W. Jiang, Y. Zhai, H. Li, and R. Wang
Learned Image Compression with ROI-Weighted Distortion and Bit Allocation
2024
URL, RIS, BibTex

P. Philippe, T. Ladune, S. Davenet, and T. Leguay
ED: Perceptually tuned Enhanced Compression Model
2024
URL, RIS, BibTex

T. Ladune, P. Philippe, G. Clare, F. Henry, and T. Leguay
Cool-Chic: Perceptually Tuned Low Complexity Overfitted Image Coder
2024
URL, RIS, BibTex

M. Fischer, P. Neher, P. Schüffler, S. Xiao, S. D. Almeida, C. Ulrich, A. Muckenhuber, R. Braren, et al.
Enhanced Diagnostic Fidelity in Pathology Whole Slide Image Compression via Deep Learning
Machine Learning in Medical Imaging, 2023
DOI, RIS, BibTex


Sponsored by