244 citations · 772 across the 26 of their papers we have counts for
8 papers · 1 filter
Bandwidth-efficient Inference for Neural Image Compression
Shanzhi Yin, Tongda Xu, Yongsheng Liang +4
With neural networks growing deeper and feature maps growing larger, limited communication bandwidth with external memory (or DRAM) and power constraints become a bottleneck in imp…
Conditional Perceptual Quality Preserving Image Compression
Tongda Xu, Qian Zhang, Yanghao Li +7
We propose conditional perceptual quality, an extension of the perceptual quality defined in \citet{blau2018perception}, by conditioning it on user defined information. Specificall…
R-MAE: Regions Meet Masked Autoencoders
Duy-Kien Nguyen, Vaibhav Aggarwal, Yanghao Li +4
In this work, we explore regions as a potential visual analogue of words for self-supervised image representation learning. Inspired by Masked Autoencoding (MAE), a generative pre-…
Hiera: A Hierarchical Vision Transformer without the Bells-and-Whistles
Chaitanya Ryali, Yuan-Ting Hu, Daniel Bolya +10
Modern hierarchical vision transformers have added several vision-specific components in the pursuit of supervised classification performance. While these components lead to effect…
Evaluating Strong Idempotence of Image Codec
Qian Zhang, Tongda Xu, Yanghao Li +1
In this paper, we first propose the concept of strong idempotent codec based on idempotent codec. The idempotence of codec refers to the stability of codec to re-compression. Simil…
Diffusion Models as Masked Autoencoders
Chen Wei, Karttikeya Mangalam, Po-Yao Huang +7
There has been a longstanding belief that generation can facilitate a true understanding of visual data. In line with this, we revisit generatively pre-training visual representati…
Efficient Semantic Segmentation by Altering Resolutions for Compressed Videos
Yubin Hu, Yuze He, Yanghao Li +4
Video semantic segmentation (VSS) is a computationally expensive task due to the per-frame prediction for videos of high frame rates. In recent work, compact models or adaptive net…
Reversible Vision Transformers
Karttikeya Mangalam, Haoqi Fan, Yanghao Li +4
We present Reversible Vision Transformers, a memory efficient architecture design for visual recognition. By decoupling the GPU memory requirement from the depth of the model, Reve…