activity
20142026
most citedVisual Instruction Tuning

699 citations · 2.1k across the 49 of their papers we have counts for

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Showing 2017Show all

7 papers · 1 filter

cs.CV2017★ 4 cited

Video Object Detection with an Aligned Spatial-Temporal Memory

Fanyi Xiao, Yong Jae Lee

We introduce Spatial-Temporal Memory Networks for video object detection. At its core, a novel Spatial-Temporal Memory module (STMM) serves as the recurrent computation unit to mod…

cs.CV2017★ 4 cited

Cross-Domain Self-supervised Multi-task Feature Learning using Synthetic Imagery

Zhongzheng Ren, Yong Jae Lee

In human learning, it is common to use multiple sources of information jointly. However, most existing feature learning approaches learn from only a single task. In this paper, we…

cs.CV2017★ 21 cited

Weakly-supervised Visual Grounding of Phrases with Linguistic Structures

Fanyi Xiao, Leonid Sigal, Yong Jae Lee

We propose a weakly-supervised approach that takes image-sentence pairs as input and learns to visually ground (i.e., localize) arbitrary linguistic phrases, in the form of spatial…

cs.CV2017★ 6 cited

Who Will Share My Image? Predicting the Content Diffusion Path in Online Social Networks

Wenjian Hu, Krishna Kumar Singh, Fanyi Xiao +3

Content popularity prediction has been extensively studied due to its importance and interest for both users and hosts of social media sites like Facebook, Instagram, Twitter, and…

cs.CV2017★ 5 cited

Identifying First-person Camera Wearers in Third-person Videos

Chenyou Fan, Jangwon Lee, Mingze Xu +4

We consider scenarios in which we wish to perform joint scene understanding, object tracking, activity recognition, and other tasks in environments in which multiple people are wea…

cs.CV2017★ 4 cited

Interspecies Knowledge Transfer for Facial Keypoint Detection

Maheen Rashid, Xiuye Gu, Yong Jae Lee

We present a method for localizing facial keypoints on animals by transferring knowledge gained from human faces. Instead of directly finetuning a network trained to detect keypoin…

cs.CV2017

Hide-and-Seek: Forcing a Network to be Meticulous for Weakly-supervised Object and Action Localization

Krishna Kumar Singh, Yong Jae Lee

We propose `Hide-and-Seek', a weakly-supervised framework that aims to improve object localization in images and action localization in videos. Most existing weakly-supervised meth…