What is Where by Looking: Weakly-Supervised Open-World Phrase-Grounding
without Text Inputs

What is Where by Looking: Weakly-Supervised Open-World Phrase-Grounding without Text Inputs

19 June 2022

Tal Shaharabany

Lior Wolf

Papers citing "What is Where by Looking: Weakly-Supervised Open-World Phrase-Grounding without Text Inputs"

8 / 8 papers shown

Title
Auto-Vocabulary Semantic Segmentation Osman Ülger Maksymilian Kulicki Yuki M. Asano Martin R. Oswald VLM 29 2 0 07 Dec 2023
Spatial-Aware Token for Weakly Supervised Object Localization Ping Wu Wei Zhai Yang Cao Jiebo Luo Zhengjun Zha WSOL 19 9 0 18 Mar 2023
BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation Junnan Li Dongxu Li Caiming Xiong S. Hoi MLLM BDL VLM CLIP 382 4,010 0 28 Jan 2022
Text2Mesh: Text-Driven Neural Stylization for Meshes O. Michel Roi Bar-On Richard Liu Sagie Benaim Rana Hanocka CLIP AI4CE 175 350 0 06 Dec 2021
Mind the Gap: Domain Gap Control for Single Shot Domain Adaptation for Generative Adversarial Networks Peihao Zhu Rameen Abdal John C. Femiani Peter Wonka GAN 132 80 0 15 Oct 2021
Learning to Prompt for Vision-Language Models Kaiyang Zhou Jingkang Yang Chen Change Loy Ziwei Liu VPVLM CLIP VLM 322 2,108 0 02 Sep 2021
HarDNet: A Low Memory Traffic Network P. Chao Chao-Yang Kao Yunxing Ruan Chien-Hsiang Huang Y. Lin 188 263 0 03 Sep 2019
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand M. Andreetto Hartwig Adam 3DH 948 20,214 0 17 Apr 2017