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LossAgent: Towards Any Optimization Objectives for Image Processing with LLM Agents
Bingchen Li, Xin Li, Yiting Lu +1
We present the first loss agent, dubbed LossAgent, for low-level image processing tasks, e.g., image super-resolution and restoration, intending to achieve any customized optimizat…
MambaCSR: Dual-Interleaved Scanning for Compressed Image Super-Resolution With SSMs
Yulin Ren, Xin Li, Mengxi Guo +3
We present MambaCSR, a simple but effective framework based on Mamba for the challenging compressed image super-resolution (CSR) task. Particularly, the scanning strategies of Mamb…
UCIP: A Universal Framework for Compressed Image Super-Resolution using Dynamic Prompt
Xin Li, Bingchen Li, Yeying Jin +4
Compressed Image Super-resolution (CSR) aims to simultaneously super-resolve the compressed images and tackle the challenging hybrid distortions caused by compression. However, exi…
PromptCIR: Blind Compressed Image Restoration with Prompt Learning
Bingchen Li, Xin Li, Yiting Lu +5
Blind Compressed Image Restoration (CIR) has garnered significant attention due to its practical applications. It aims to mitigate compression artifacts caused by unknown quality f…
Is Vanilla MLP in Neural Radiance Field Enough for Few-shot View Synthesis?
Hanxin Zhu, Tianyu He, Xin Li +2
Neural Radiance Field (NeRF) has achieved superior performance for novel view synthesis by modeling the scene with a Multi-Layer Perception (MLP) and a volume rendering procedure,…