Compressing Images with Neural Networks
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Compressing Images with Neural Networks
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Re: Compressing Images with Neural Networks
#2The interesting diagram to me is the last one, for computational cost, which shows the 10x penalty of the ML-based codecs.
Re: Compressing Images with Neural Networks
#3It is not going to take off if it is not significantly better, and has browser support. WebP took off thanks to Chrome, while JPEG2000 floundered. If not native browser support, maybe the codec could be shipped by WASM or something? The interesting diagram to me is the last one, for computational cost, which shows the 10x penalty of the ML-based codecs.
Re: Compressing Images with Neural Networks
#4It is not going to take off if it is not significantly better, and has browser support. WebP took off thanks to Chrome, while JPEG2000 floundered. If not native browser support, maybe the codec could be shipped by WASM or something? The interesting diagram to me is the last one, for computational cost, which shows the 10x penalty of the ML-based codecs.
Re: Compressing Images with Neural Networks
#5It is not going to take off if it is not significantly better, and has browser support. WebP took off thanks to Chrome, while JPEG2000 floundered. If not native browser support, maybe the codec could be shipped by WASM or something? The interesting diagram to me is the last one, for computational cost, which shows the 10x penalty of the ML-based codecs.
Re: Compressing Images with Neural Networks
#6It is not going to take off if it is not significantly better, and has browser support. WebP took off thanks to Chrome, while JPEG2000 floundered. If not native browser support, maybe the codec could be shipped by WASM or something? The interesting diagram to me is the last one, for computational cost, which shows the 10x penalty of the ML-based codecs.
Did JPEG2000 really flounder? If your concept of it being a consumer facing product as a direct replacement for JPEG, then I could see being unsuccessful in that respect. However, JPEG2000 has found its place in the professional side of things.
One problem is that without broad adoption, support even in niche cases is precarious; the ecosystem is smaller. That makes the codec not safe for archiving, only for distribution.
The strongest use case I see for this is streaming video, where the demand for compression is highest.
Re: Compressing Images with Neural Networks
#7Earlier quoted context omitted.
Did JPEG2000 really flounder? If your concept of it being a consumer facing product as a direct replacement for JPEG, then I could see being unsuccessful in that respect. However, JPEG2000 has found its place in the professional side of things.
Yes, I do mean broad- rather than niche adoption. I myself used J2K to archive film scans. One problem is that without broad adoption, support even in niche cases is precarious; the ecosystem is smaller. That makes the codec not safe for archiving, only for distribution. The strongest use case I see for this is streaming video, where the demand for compression is highest.
Re: Compressing Images with Neural Networks
#8It is not going to take off if it is not significantly better, and has browser support. WebP took off thanks to Chrome, while JPEG2000 floundered. If not native browser support, maybe the codec could be shipped by WASM or something? The interesting diagram to me is the last one, for computational cost, which shows the 10x penalty of the ML-based codecs.