Shuyun Wang, Shangchen Zhou, Peiqing Yang, Yuekun Dai, Xin Yu and Chen Change Loy · Efficient 4K matting

MatAnyone-E

MatAnyone-E is an efficient extension of MatAnyone 2 for high-resolution video matting, described in a paper by Shuyun Wang and co-authors (arXiv:2610.35724). It keeps the MatAnyone 2 architecture but replaces the two parts whose cost grows fastest with resolution. Sparse Memory Propagation first runs a cheap low-resolution pass, uses its uncertainty to select the query locations needing detail and its affinities to select the most relevant memory, then runs high-resolution matching only on those query-memory pairs. A lightweight decoder, designed from stage-wise latency profiling and trained by feature distillation from the original decoder, further cuts decoding cost. The authors report quality comparable to MatAnyone 2, with MAD (×10³) of 4.14 against 4.10 on VideoMatte HR, 1.62 against 1.61 on YouTubeMatte HR and 4.28 against 4.24 on CRGNN. At 4K they report an estimated 7.4× inference speedup and peak GPU memory at 7.6% of MatAnyone 2. With compilation on a single NVIDIA H200 it reaches 73.07 FPS at 1080p and 28.62 FPS at 4K. The page gives no licence, code release or version information.