Qifeng Chen, Xin Yang, Ying-Cong Chen, Chenyang Qi, Ka Leong Cheng
We lifted 7 functions out of this paper's own repositories and ran 3 of them in a sandbox. "Ran" means the function executed on a synthesized input and returned a value. It is not a reproduction of the paper's results.
| Repository | Role | Ran |
|---|---|---|
| abnervictor/hyperthumbnail | canonical | 3 of 7 |
| Function | Status | Where it lives |
|---|---|---|
| get_act_function | Ran | abnervictor/hyperthumbnail/src/ops/modules.py code served (permissive licence) · get_code("9c15d12caa8e49d1") |
| get_norm_function | Ran | abnervictor/hyperthumbnail/src/ops/modules.py code served (permissive licence) · get_code("a4c0a276281ee685") |
| noise_round | Ran | abnervictor/hyperthumbnail/src/ops/compression_modules.py code served (permissive licence) · get_code("db467a9af41459ff") |
| AttentionBlock | Not yet run | abnervictor/hyperthumbnail/BasicSR/basicsr/archs/dfdnet_util.py code served (permissive licence) · get_code("8d3cd21cd5c3181a") |
| adaptive_instance_normalization | Not yet run | abnervictor/hyperthumbnail/BasicSR/basicsr/archs/dfdnet_util.py code served (permissive licence) · get_code("b7c6741eed724350") |
| calc_mean_std | Not yet run | abnervictor/hyperthumbnail/BasicSR/basicsr/archs/dfdnet_util.py code served (permissive licence) · get_code("a7e8af4ef5efc131") |
| get_part_location | Not yet run | abnervictor/hyperthumbnail/BasicSR/inference/inference_dfdnet.py code served (permissive licence) · get_code("9adf4d768799f874") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
Contemporary image rescaling aims at embedding a high-resolution (HR) image into a low-resolution (LR) thumbnail image that contains embedded information for HR image reconstruction. Unlike traditional image superresolution, this enables high-fidelity HR image restoration faithful to the original one, given the embedded information in the LR thumbnail. However, state-of-the-art image rescaling methods do not optimize the LR image file size for efficient sharing and fall short of real-time performance for ultra-high-resolution (e.g., 6K) image reconstruction. To address these two challenges, we propose a novel framework (HyperThumbnail) for real-time 6K rate-distortionaware image rescaling. Our framework first embeds an HR image into a JPEG LR thumbnail by an encoder with our proposed quantization prediction module, which minimizes the file size of the embedding LR JPEG thumbnail while maximizing HR reconstruction quality. Then, an efficient frequency-aware decoder reconstructs a high-fidelity HR image from the LR one in real time. Extensive experiments demonstrate that our framework outperforms previous image rescaling baselines in rate-distortion performance and can perform 6K image reconstruction in real time.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("2304.01064")
get_code_for_paper("2304.01064")
have("2304.01064")
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