493 citations · 593 across the 8 of their papers we have counts for
8 papers
Window Attention is Bugged: How not to Interpolate Position Embeddings
Daniel Bolya, Chaitanya Ryali, Judy Hoffman +1
Window attention, position embeddings, and high resolution finetuning are core concepts in the modern transformer era of computer vision. However, we find that naively combining th…
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…
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…
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…
Multiview Compressive Coding for 3D Reconstruction
Chao-Yuan Wu, Justin Johnson, Jitendra Malik +2
A central goal of visual recognition is to understand objects and scenes from a single image. 2D recognition has witnessed tremendous progress thanks to large-scale learning and ge…
MViTv2: Improved Multiscale Vision Transformers for Classification and Detection
Yanghao Li, Chao-Yuan Wu, Haoqi Fan +4
In this paper, we study Multiscale Vision Transformers (MViTv2) as a unified architecture for image and video classification, as well as object detection. We present an improved ve…