11 citations · 27 across the 6 of their papers we have counts for
6 papers
Davidsonian Scene Graph: Improving Reliability in Fine-grained Evaluation for Text-to-Image Generation
Jaemin Cho, Yushi Hu, Roopal Garg +6
Evaluating text-to-image models is notoriously difficult. A strong recent approach for assessing text-image faithfulness is based on QG/A (question generation and answering), which…
Scaling Robot Learning with Semantically Imagined Experience
Tianhe Yu, Ted Xiao, Austin Stone +10
Recent advances in robot learning have shown promise in enabling robots to perform a variety of manipulation tasks and generalize to novel scenarios. One of the key contributing fa…
Imagen Editor and EditBench: Advancing and Evaluating Text-Guided Image Inpainting
Su Wang, Chitwan Saharia, Ceslee Montgomery +11
Text-guided image editing can have a transformative impact in supporting creative applications. A key challenge is to generate edits that are faithful to input text prompts, while…
A New Path: Scaling Vision-and-Language Navigation with Synthetic Instructions and Imitation Learning
Aishwarya Kamath, Peter Anderson, Su Wang +6
Recent studies in Vision-and-Language Navigation (VLN) train RL agents to execute natural-language navigation instructions in photorealistic environments, as a step towards robots…
Less is More: Generating Grounded Navigation Instructions from Landmarks
Su Wang, Ceslee Montgomery, Jordi Orbay +7
We study the automatic generation of navigation instructions from 360-degree images captured on indoor routes. Existing generators suffer from poor visual grounding, causing them t…
On the Evaluation of Vision-and-Language Navigation Instructions
Ming Zhao, Peter Anderson, Vihan Jain +4
Vision-and-Language Navigation wayfinding agents can be enhanced by exploiting automatically generated navigation instructions. However, existing instruction generators have not be…