July 25, 2022, 1:12 a.m. | Zhengcong Fei, Junshi Huang, Xiaoming Wei, Xiaolin Wei

cs.CV updates on arXiv.org arxiv.org

Existing approaches to image captioning usually generate the sentence
word-by-word from left to right, with the constraint of conditioned on local
context including the given image and history generated words. There have been
many studies target to make use of global information during decoding, e.g.,
iterative refinement. However, it is still under-explored how to effectively
and efficiently incorporate the future context. To respond to this issue,
inspired by that Non-Autoregressive Image Captioning (NAIC) can leverage
two-side relation with modified mask …

arxiv captioning context cv future image modeling

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Data Integration Specialist

@ Accenture Federal Services | San Antonio, TX

Geospatial Data Engineer - Location Intelligence

@ Allegro | Warsaw, Poland

Site Autonomy Engineer (Onsite)

@ May Mobility | Tokyo, Japan

Summer Intern, AI (Artificial Intelligence)

@ Nextech Systems | Tampa, FL

Permitting Specialist/Wetland Scientist

@ AECOM | Chelmsford, MA, United States