activity
20182025
most citedOpen-Vocabulary Semantic Segmentation with Mask-adapted CLIP

10 citations · 20 across the 6 of their papers we have counts for

collaborators

9 papers

cs.CV2025

MapReduce LoRA: Advancing the Pareto Front in Multi-Preference Optimization for Generative Models

Chieh-Yun Chen, Zhonghao Wang, Qi Chen +10

Reinforcement learning from human feedback (RLHF) with reward models has advanced alignment of generative models to human aesthetic and perceptual preferences. However, jointly opt…

cs.CV2022★ 10 cited

Open-Vocabulary Semantic Segmentation with Mask-adapted CLIP

Feng Liang, Bichen Wu, Xiaoliang Dai +6

Open-vocabulary semantic segmentation aims to segment an image into semantic regions according to text descriptions, which may not have been seen during training. Recent two-stage…

cs.CV2021★ 8 cited

Generalized Few-Shot Semantic Segmentation: All You Need is Fine-Tuning

Josh Myers-Dean, Yinan Zhao, Brian Price +2

Generalized few-shot semantic segmentation was introduced to move beyond only evaluating few-shot segmentation models on novel classes to include testing their ability to remember…

cs.CV2020

Objectness-Aware Few-Shot Semantic Segmentation

Yinan Zhao, Brian Price, Scott Cohen +1

Few-shot semantic segmentation models aim to segment images after learning from only a few annotated examples. A key challenge for them is how to avoid overfitting because limited…

cs.CV2020

Assessing Image Quality Issues for Real-World Problems

Tai-Yin Chiu, Yinan Zhao, Danna Gurari

We introduce a new large-scale dataset that links the assessment of image quality issues to two practical vision tasks: image captioning and visual question answering. First, we id…

cs.CV2020

Captioning Images Taken by People Who Are Blind

Danna Gurari, Yinan Zhao, Meng Zhang +1

While an important problem in the vision community is to design algorithms that can automatically caption images, few publicly-available datasets for algorithm development directly…

cs.CV2019

Unconstrained Foreground Object Search

Yinan Zhao, Brian Price, Scott Cohen +1

Many people search for foreground objects to use when editing images. While existing methods can retrieve candidates to aid in this, they are constrained to returning objects that…

cs.CV2019

Predicting How to Distribute Work Between Algorithms and Humans to Segment an Image Batch

Danna Gurari, Yinan Zhao, Suyog Dutt Jain +2

Foreground object segmentation is a critical step for many image analysis tasks. While automated methods can produce high-quality results, their failures disappoint users in need o…

cs.CV2018★ 2 cited

Guided Image Inpainting: Replacing an Image Region by Pulling Content from Another Image

Yinan Zhao, Brian Price, Scott Cohen +1

Deep generative models have shown success in automatically synthesizing missing image regions using surrounding context. However, users cannot directly decide what content to synth…