… To arrive at CC12M, we keep the image-text filtering intact, and relax the unimodal filters …
Second, in text-based filtering, we allow text between 3 and 256 words in the alt-text. We still …

… Yvan Leclerc and Pascal Fua, colleagues from my brief interlude at SRI International, gave
me new perspectives on alternative approaches to computer vision. During my six years of …

… In this work, we leverage a dataset of over one billion noisy image alt-text pairs to scale
visual and vision-language representation learning. We follow the procedures described in the …

… We collect 4 billion image and alt-text pairs following the same process as ALIGN [30],
with the same image-based filtering but simpler text-based filtering. Appendix L shows that …

… We remove the alt-text if any of its unigrams cannot be found in the vocabulary. Afterwards,
… 200 million images, each corresponding to one alt-text. The word cloud of 200 most frequent …

… With the rise and development of deep learning, computer vision has been tremendously
transformed and reshaped. As an important research area in computer vision, scene text …

… For many computer vision applications such as image captioning, … and text level is an
essential yet challenging problem. Its challenges originate from the large word variance in the text …

We present a method for zero-shot, text-driven editing of natural images and videos. Given
an image or a video and a text prompt, our goal is to edit the appearance of existing objects (…

… As an alternative, we propose learning visual grounding from freely-available internet data,
… alt-text captured in the Conceptual Captions dataset [24], containing around 3.3M image-text …

… shared representation, we introduce a new computer vision foundation model, Florence, to
… image-text data, our Florence model can be easily adapted for various computer vision tasks…