2.1k citations · 2.4k across the 9 of their papers we have counts for
9 papers
Guiding Image Captioning Models Toward More Specific Captions
Simon Kornblith, Lala Li, Zirui Wang +1
Image captioning is conventionally formulated as the task of generating captions for images that match the distribution of reference image-caption pairs. However, reference caption…
FIT: Far-reaching Interleaved Transformers
Ting Chen, Lala Li
We present FIT: a transformer-based architecture with efficient self-attention and adaptive computation. Unlike original transformers, which operate on a single sequence of data to…
A Generalist Framework for Panoptic Segmentation of Images and Videos
Ting Chen, Lala Li, Saurabh Saxena +2
Panoptic segmentation assigns semantic and instance ID labels to every pixel of an image. As permutations of instance IDs are also valid solutions, the task requires learning of hi…
A Unified Sequence Interface for Vision Tasks
Ting Chen, Saurabh Saxena, Lala Li +3
While language tasks are naturally expressed in a single, unified, modeling framework, i.e., generating sequences of tokens, this has not been the case in computer vision. As a res…
Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding
Chitwan Saharia, William Chan, Saurabh Saxena +11
We present Imagen, a text-to-image diffusion model with an unprecedented degree of photorealism and a deep level of language understanding. Imagen builds on the power of large tran…
Pix2seq: A Language Modeling Framework for Object Detection
Ting Chen, Saurabh Saxena, Lala Li +2
We present Pix2Seq, a simple and generic framework for object detection. Unlike existing approaches that explicitly integrate prior knowledge about the task, we cast object detecti…