Joon-Young Lee

research

∙ 09/07/2023

Tracking Anything with Decoupled Video Segmentation

Training data for video segmentation are expensive to annotate. This imp...

0 Ho Kei Cheng, et al. ∙

research

∙ 08/18/2023

Long-range Multimodal Pretraining for Movie Understanding

Learning computer vision models from (and for) movies has a long-standin...

0 Dawit Mureja Argaw, et al. ∙

research

∙ 07/29/2023

XMem++: Production-level Video Segmentation From Few Annotated Frames

Despite advancements in user-guided video segmentation, extracting compl...

0 Maksym Bekuzarov, et al. ∙

research

∙ 07/15/2023

INVE: Interactive Neural Video Editing

We present Interactive Neural Video Editing (INVE), a real-time video ed...

0 Jiahui Huang, et al. ∙

research

∙ 12/20/2022

Tracking by Associating Clips

The tracking-by-detection paradigm today has become the dominant method ...

0 Sanghyun Woo, et al. ∙

research

∙ 12/20/2022

Bridging Images and Videos: A Simple Learning Framework for Large Vocabulary Video Object Detection

Scaling object taxonomies is one of the important steps toward a robust ...

0 Sanghyun Woo, et al. ∙

research

∙ 11/22/2022

Videogenic: Video Highlights via Photogenic Moments

This paper investigates the challenge of extracting highlight moments fr...

0 David Chuan-En Lin, et al. ∙

research

∙ 11/22/2022

VideoMap: Video Editing in Latent Space

Video has become a dominant form of media. However, video editing interf...

0 David Chuan-En Lin, et al. ∙

research

∙ 11/16/2022

A Generalized Framework for Video Instance Segmentation

Recently, handling long videos of complex and occluded sequences has eme...

0 Miran Heo, et al. ∙

research

∙ 08/03/2022

Per-Clip Video Object Segmentation

Recently, memory-based approaches show promising results on semi-supervi...

0 KwanYong Park, et al. ∙

research

∙ 07/27/2022

One-Trimap Video Matting

Recent studies made great progress in video matting by extending the suc...

0 Hongje Seong, et al. ∙

research

∙ 07/20/2022

The Anatomy of Video Editing: A Dataset and Benchmark Suite for AI-Assisted Video Editing

Machine learning is transforming the video editing industry. Recent adva...

0 Dawit Mureja Argaw, et al. ∙

research

∙ 06/09/2022

VITA: Video Instance Segmentation via Object Token Association

We introduce a novel paradigm for offline Video Instance Segmentation (V...

0 Miran Heo, et al. ∙

research

∙ 01/10/2022

Information-Theoretic Bias Reduction via Causal View of Spurious Correlation

We propose an information-theoretic bias measurement technique through a...

0 Seonguk Seo, et al. ∙

research

∙ 09/23/2021

Hierarchical Memory Matching Network for Video Object Segmentation

We present Hierarchical Memory Matching Network (HMMN) for semi-supervis...

9 Hongje Seong, et al. ∙

research

∙ 09/02/2021

Studying the Effects of Self-Attention for Medical Image Analysis

When the trained physician interprets medical images, they understand th...

0 Adrit Rao, et al. ∙

research

∙ 08/06/2021

Unsupervised Learning of Debiased Representations with Pseudo-Attributes

Dataset bias is a critical challenge in machine learning, and its negati...

0 Seonguk Seo, et al. ∙

research

∙ 06/17/2021

Learning to Associate Every Segment for Video Panoptic Segmentation

Temporal correspondence - linking pixels or objects across frames - is a...

0 Sanghyun Woo, et al. ∙

research

∙ 06/03/2021

APES: Audiovisual Person Search in Untrimmed Video

Humans are arguably one of the most important subjects in video streams,...

0 Juan Leon Alcazar, et al. ∙

research

∙ 05/30/2021

Polygonal Point Set Tracking

In this paper, we propose a novel learning-based polygonal point set tra...

0 Gunhee Nam, et al. ∙

research

∙ 05/18/2021

Exemplar-Based Open-Set Panoptic Segmentation Network

We extend panoptic segmentation to the open-world and introduce an open-...

0 Jaedong Hwang, et al. ∙

research

∙ 06/19/2020

Video Panoptic Segmentation

Panoptic segmentation has become a new standard of visual recognition ta...

0 Dahun Kim, et al. ∙

research

∙ 05/20/2020

Active Speakers in Context

Current methods for active speak er detection focus on modeling short-te...

0 Juan Leon Alcazar, et al. ∙

research

∙ 05/08/2020

History for Visual Dialog: Do we really need it?

Visual Dialog involves "understanding" the dialog history (what has been...

2 Shubham Agarwal, et al. ∙

research

∙ 03/20/2020

DMV: Visual Object Tracking via Part-level Dense Memory and Voting-based Retrieval

We propose a novel memory-based tracker via part-level dense memory and ...

0 Gunhee Nam, et al. ∙

research

∙ 08/23/2019

Onion-Peel Networks for Deep Video Completion

We propose the onion-peel networks for video completion. Given a set of ...

4 Seoung Wug Oh, et al. ∙

research

∙ 05/30/2019

Align-and-Attend Network for Globally and Locally Coherent Video Inpainting

We propose a novel feed-forward network for video inpainting. We use a s...

0 Sanghyun Woo, et al. ∙

research

∙ 05/20/2019

Learning Video Representations from Correspondence Proposals

Correspondences between frames encode rich information about dynamic con...

0 Xingyu Liu, et al. ∙

research

∙ 05/08/2019

Deep Blind Video Decaptioning by Temporal Aggregation and Recurrence

Blind video decaptioning is a problem of automatically removing text ove...

0 Dahun Kim, et al. ∙

research

∙ 05/05/2019

Deep Video Inpainting

Video inpainting aims to fill spatio-temporal holes with plausible conte...

0 Dahun Kim, et al. ∙

research

∙ 04/22/2019

Fast User-Guided Video Object Segmentation by Interaction-and-Propagation Networks

We present a deep learning method for the interactive video object segme...

14 Seoung Wug Oh, et al. ∙

research

∙ 04/01/2019

Video Object Segmentation using Space-Time Memory Networks

We propose a novel solution for semi-supervised video object segmentatio...

0 Seoung Wug Oh, et al. ∙

research

∙ 09/21/2018

GAPLE: Generalizable Approaching Policy LEarning for Robotic Object Searching in Indoor Environment

We study the problem of learning a generalizable action policy for an in...

0 Xin Ye, et al. ∙

research

∙ 08/07/2018

Contemplating Visual Emotions: Understanding and Overcoming Dataset Bias

While machine learning approaches to visual emotion recognition offer gr...

4 Rameswar Panda, et al. ∙

research

∙ 07/17/2018

CBAM: Convolutional Block Attention Module

We propose Convolutional Block Attention Module (CBAM), a simple yet eff...

0 Sanghyun Woo, et al. ∙

research

∙ 07/17/2018

BAM: Bottleneck Attention Module

Recent advances in deep neural networks have been developed via architec...

0 Jongchan Park, et al. ∙

research

∙ 04/12/2018

Distort-and-Recover: Color Enhancement using Deep Reinforcement Learning

Learning-based color enhancement approaches typically learn to map from ...

0 Jongchan Park, et al. ∙

research

∙ 02/24/2018

The AdobeIndoorNav Dataset: Towards Deep Reinforcement Learning based Real-world Indoor Robot Visual Navigation

Deep reinforcement learning (DRL) demonstrates its potential in learning...

0 Kaichun Mo, et al. ∙

research

∙ 09/29/2017

Photometric Stabilization for Fast-forward Videos

Videos captured by consumer cameras often exhibit temporal variations in...

0 Xuaner Cecilia Zhang, et al. ∙

research

∙ 08/24/2017

Gradient-based Camera Exposure Control for Outdoor Mobile Platforms

We introduce a novel method to automatically adjust camera exposure for ...

0 Inwook Shim, et al. ∙

research

∙ 12/22/2016

Physically-Based Rendering for Indoor Scene Understanding Using Convolutional Neural Networks

Indoor scene understanding is central to applications such as robot navi...

0 Yinda Zhang, et al. ∙

research

∙ 12/20/2016

Action-Driven Object Detection with Top-Down Visual Attentions

A dominant paradigm for deep learning based object detection relies on a...

0 Donggeun Yoo, et al. ∙

research

∙ 03/24/2016

Fine-scale Surface Normal Estimation using a Single NIR Image

We present surface normal estimation using a single near infrared (NIR) ...

0 Youngjin Yoon, et al. ∙

research

∙ 11/12/2015

Automatic Content-Aware Color and Tone Stylization

We introduce a new technique that automatically generates diverse, visua...

0 Joon-Young Lee, et al. ∙

research

∙ 06/25/2015

AttentionNet: Aggregating Weak Directions for Accurate Object Detection

We present a novel detection method using a deep convolutional neural ne...

0 Donggeun Yoo, et al. ∙

research

∙ 12/04/2014

Fisher Kernel for Deep Neural Activations

Compared to image representation based on low-level local descriptors, d...

0 Donggeun Yoo, et al. ∙

Joon-Young Lee

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