4 accepted papers
Zero-shot neural architecture search (NAS) has shown great potential in designing image recognition networks for its high efficiency and low resource consumption. However, most of the existing zero-shot NAS methods fail to utilize prior information in datasets when calculating the score of candidate…
Recently, Transformers have shown impressive performance in image super-resolution (SR), due to exploiting strong representation ability of multi-head self-attention (MSA). However, existing methods typically calculate MSA in a single range and granularity, preventing the model from capturing suffic…
Deep neural networks have witnessed great success in Single Image Super-Resolution (SISR). However, current improvements are mainly contributed by much deeper networks, which leads to huge computation cost and limited application for mobile devices. Moreover, most existing methods propagate the basi…
In recent years, part-based models have been verified their effectiveness for person Re-identification (Re-ID). Since they learn an embedding only by partitioning single-scale features of the highest layer in the backbone network, their performances highly depend on the well-aligned parts of the ext…