illustration of a green net
October 11, 2021 – October 17, 2021

Microsoft at ICCV 2021

位置: Virtual

Microsoft Research ブログ

On the left, a diagram with three layers, each of which contains a half-transparent image processed from the same image. The processed images are partitioned into several grids, and each grid contains 4 x 4 image patches. From bottom to top, the number of grids in each layer are 4 x 4, 2 x 2, and 1 x 1, respectively. The layers are labeled “4x,” “8x,” and “16x,” respectively, from bottom to top. An arrow joining the three layers points upward to the words “Segmentation” and “Detection” and an ellipsis. Another arrow points from the top layer to the word “classification.” On the right, a bar chart with a blue bar labeled “Swin V1” and an orange bar labeled “Swin V2.” The orange bar is much taller and labeled “3 billion (1,536 x 1,536 resolution)”; the blue bar is labeled “197 million.” An arrow labeled “15x” points upward from the blue bar, indicating the orange bar is 15 times higher than the blue one.
Microsoft Research ブログ

| Han Hu と Baining Guo

Early last year, our research team from …

An image generation model training using MVM. Images show a panda progressively being generated to become more realistic, various paintings generated by the model, an anime character generated to become more realistic, and various cat images generated to become more realistic.
Microsoft Research ブログ

| Mengyu Dai と Junwon Park

Generative image models offer a unique v…

ACAV100M text on top of a series of small images.
Microsoft Research ブログ

| Yale Song

The natural association between visual o…

On left, text reads ORBIT benchmark dataset: 77 blind and low-vision collectors, 486 objects, 3822 videos, and 2687934 frames. On right, a graphic of a face mask with a line that connects to a picture of a cloth mask with a black and white zig-zag pattern. The line reads seven to eight videos per object. Below the face mask graphic, there are three yellow objects resembling a watering can, a key, and a comb. A line next to these reads two to ten objects per user. The objects are falling into a green bucket, with a line to the right of the bucket that reads user’s bucket.
Microsoft Research ブログ

| Daniela Massiceti, Cecily Morrison, Katja Hofmann, と Ed Cutrell

Object recognition systems have made spe…