99 citations · 225 across the 33 of their papers we have counts for
37 papers
ViTAL-X: Video-Text Alignment with Cross-Modal Temporal Edits
Sethuraman T, Savya Khosla, Onkar Kishor Susladkar +6
Video-text models adapted from image-text architectures (e.g., CLIP) frequently exhibit temporal blindness, the inability to perceive fundamental cues like order, direction, and mo…
Unified Video Dense Prediction from Disjoint Data
Yihong Sun, Seoung Wug Oh, Jiahui Huang +2
Scene understanding requires simultaneous prediction about geometry, appearance, and semantics. However, existing task-specific annotations are fragmented across incompatible, doma…
DAGE: Dual-Stream Architecture for Efficient and Fine-Grained Geometry Estimation
Tuan Duc Ngo, Jiahui Huang, Seoung Wug Oh +4
Estimating accurate, view-consistent geometry and camera poses from uncalibrated multi-view/video inputs remains challenging - especially at high spatial resolutions and over long…
VideoMaMa: Mask-Guided Video Matting via Generative Prior
Sangbeom Lim, Seoung Wug Oh, Jiahui Huang +3
Generalizing video matting models to real-world videos remains a significant challenge due to the scarcity of labeled data. To address this, we present Video Mask-to-Matte Model (V…
FRAME: Pre-Training Video Feature Representations via Anticipation and Memory
Sethuraman TV, Savya Khosla, Vignesh Srinivasakumar +5
Dense video prediction tasks, such as object tracking and semantic segmentation, require video encoders that generate temporally consistent, spatially dense features for every fram…
Tuning-Free Multi-Event Long Video Generation via Synchronized Coupled Sampling
Subin Kim, Seoung Wug Oh, Jui-Hsien Wang +2
While recent advancements in text-to-video diffusion models enable high-quality short video generation from a single prompt, generating real-world long videos in a single pass rema…
Elevating Flow-Guided Video Inpainting with Reference Generation
Suhwan Cho, Seoung Wug Oh, Sangyoun Lee +1
Video inpainting (VI) is a challenging task that requires effective propagation of observable content across frames while simultaneously generating new content not present in the o…
IF-MDM: Implicit Face Motion Diffusion Model for High-Fidelity Realtime Talking Head Generation
Sejong Yang, Seoung Wug Oh, Yang Zhou +1
We introduce a novel approach for high-resolution talking head generation from a single image and audio input. Prior methods using explicit face models, like 3D morphable models (3…
HARIVO: Harnessing Text-to-Image Models for Video Generation
Mingi Kwon, Seoung Wug Oh, Yang Zhou +6
We present a method to create diffusion-based video models from pretrained Text-to-Image (T2I) models. Recently, AnimateDiff proposed freezing the T2I model while only training tem…
MaGGIe: Masked Guided Gradual Human Instance Matting
Chuong Huynh, Seoung Wug Oh, Abhinav Shrivastava +1
Human matting is a foundation task in image and video processing, where human foreground pixels are extracted from the input. Prior works either improve the accuracy by additional…
VISAGE: Video Instance Segmentation with Appearance-Guided Enhancement
Hanjung Kim, Jaehyun Kang, Miran Heo +3
In recent years, online Video Instance Segmentation (VIS) methods have shown remarkable advancement with their powerful query-based detectors. Utilizing the output queries of the d…
Putting the Object Back into Video Object Segmentation
Ho Kei Cheng, Seoung Wug Oh, Brian Price +2
We present Cutie, a video object segmentation (VOS) network with object-level memory reading, which puts the object representation from memory back into the video object segmentati…
Tracking Anything with Decoupled Video Segmentation
Ho Kei Cheng, Seoung Wug Oh, Brian Price +2
Training data for video segmentation are expensive to annotate. This impedes extensions of end-to-end algorithms to new video segmentation tasks, especially in large-vocabulary set…
In-N-Out: Faithful 3D GAN Inversion with Volumetric Decomposition for Face Editing
Yiran Xu, Zhixin Shu, Cameron Smith +2
3D-aware GANs offer new capabilities for view synthesis while preserving the editing functionalities of their 2D counterparts. GAN inversion is a crucial step that seeks the latent…
Tracking by Associating Clips
Sanghyun Woo, Kwanyong Park, Seoung Wug Oh +2
The tracking-by-detection paradigm today has become the dominant method for multi-object tracking and works by detecting objects in each frame and then performing data association…
Bridging Images and Videos: A Simple Learning Framework for Large Vocabulary Video Object Detection
Sanghyun Woo, Kwanyong Park, Seoung Wug Oh +2
Scaling object taxonomies is one of the important steps toward a robust real-world deployment of recognition systems. We have faced remarkable progress in images since the introduc…
A Generalized Framework for Video Instance Segmentation
Miran Heo, Sukjun Hwang, Jeongseok Hyun +4
The handling of long videos with complex and occluded sequences has recently emerged as a new challenge in the video instance segmentation (VIS) community. However, existing method…
Per-Clip Video Object Segmentation
Kwanyong Park, Sanghyun Woo, Seoung Wug Oh +2
Recently, memory-based approaches show promising results on semi-supervised video object segmentation. These methods predict object masks frame-by-frame with the help of frequently…
One-Trimap Video Matting
Hongje Seong, Seoung Wug Oh, Brian Price +2
Recent studies made great progress in video matting by extending the success of trimap-based image matting to the video domain. In this paper, we push this task toward a more pract…
Error Compensation Framework for Flow-Guided Video Inpainting
Jaeyeon Kang, Seoung Wug Oh, Seon Joo Kim
The key to video inpainting is to use correlation information from as many reference frames as possible. Existing flow-based propagation methods split the video synthesis process i…
Cannot See the Forest for the Trees: Aggregating Multiple Viewpoints to Better Classify Objects in Videos
Sukjun Hwang, Miran Heo, Seoung Wug Oh +1
Recently, both long-tailed recognition and object tracking have made great advances individually. TAO benchmark presented a mixture of the two, long-tailed object tracking, in orde…
VITA: Video Instance Segmentation via Object Token Association
Miran Heo, Sukjun Hwang, Seoung Wug Oh +2
We introduce a novel paradigm for offline Video Instance Segmentation (VIS), based on the hypothesis that explicit object-oriented information can be a strong clue for understandin…
VISOLO: Grid-Based Space-Time Aggregation for Efficient Online Video Instance Segmentation
Su Ho Han, Sukjun Hwang, Seoung Wug Oh +4
For online video instance segmentation (VIS), fully utilizing the information from previous frames in an efficient manner is essential for real-time applications. Most previous met…
Hierarchical Memory Matching Network for Video Object Segmentation
Hongje Seong, Seoung Wug Oh, Joon-Young Lee +3
We present Hierarchical Memory Matching Network (HMMN) for semi-supervised video object segmentation. Based on a recent memory-based method [33], we propose two advanced memory rea…