141 citations · 171 across the 11 of their papers we have counts for
11 papers
PinPoint: Evaluation of Composed Image Retrieval with Explicit Negatives, Multi-Image Queries, and Paraphrase Testing
Rohan Mahadev, Joyce Yuan, Patrick Poirson +3
Composed Image Retrieval (CIR) has made significant progress, yet current benchmarks are limited to single ground-truth answers and lack the annotations needed to evaluate false po…
PinCLIP: Large-scale Foundational Multimodal Representation at Pinterest
Josh Beal, Eric Kim, Jinfeng Rao +3
While multi-modal Visual Language Models (VLMs) have demonstrated significant success across various domains, the integration of VLMs into recommendation and retrieval systems rema…
Pinterest Canvas: Large-Scale Image Generation at Pinterest
Yu Wang, Eric Tzeng, Raymond Shiau +3
While recent image generation models demonstrate a remarkable ability to handle a wide variety of image generation tasks, this flexibility makes them hard to control via prompting…
Visual Product Graph: Bridging Visual Products And Composite Images For End-to-End Style Recommendations
Yue Li Du, Ben Alexander, Mikhail Antonenka +3
Retrieving semantically similar but visually distinct contents has been a critical capability in visual search systems. In this work, we aim to tackle this problem with Visual Prod…
Large-scale Reinforcement Learning for Diffusion Models
Yinan Zhang, Eric Tzeng, Yilun Du +1
Text-to-image diffusion models are a class of deep generative models that have demonstrated an impressive capacity for high-quality image generation. However, these models are susc…
Billion-Scale Pretraining with Vision Transformers for Multi-Task Visual Representations
Josh Beal, Hao-Yu Wu, Dong Huk Park +2
Large-scale pretraining of visual representations has led to state-of-the-art performance on a range of benchmark computer vision tasks, yet the benefits of these techniques at ext…