papers

Publications (12)

cs.CV2022

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…

cs.CV2022

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…

cs.CV2024

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…

cs.CV2023

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…

cs.CV2022

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…

cs.LG2024

Hydra: Bidirectional State Space Models Through Generalized Matrix Mixers

Sukjun Hwang, Aakash Lahoti, Tri Dao +1

A wide array of sequence models are built on a framework modeled after Transformers, comprising alternating sequence mixer and channel mixer layers. This paper studies a unifying m…

cs.CV2020

Single-shot Path Integrated Panoptic Segmentation

Sukjun Hwang, Seoung Wug Oh, Seon Joo Kim

Panoptic segmentation, which is a novel task of unifying instance segmentation and semantic segmentation, has attracted a lot of attention lately. However, most of the previous met…

cs.LG2026

dnaHNet: A Scalable and Hierarchical Foundation Model for Genomic Sequence Learning

Arnav Shah, Junzhe Li, Parsa Idehpour +7

Genomic foundation models have the potential to decode DNA syntax, yet face a fundamental tradeoff in their input representation. Standard fixed-vocabulary tokenizers fragment biol…

cs.CV2021

Video Instance Segmentation using Inter-Frame Communication Transformers

Sukjun Hwang, Miran Heo, Seoung Wug Oh +1

We propose a novel end-to-end solution for video instance segmentation (VIS) based on transformers. Recently, the per-clip pipeline shows superior performance over per-frame method…

cs.CV2025

Autoregressive Universal Video Segmentation Model

Miran Heo, Sukjun Hwang, Min-Hung Chen +4

Recent video foundation models such as SAM2 excel at prompted video segmentation by treating masks as a general-purpose primitive. However, many real-world settings require unpromp…

cs.CV2025

Multi-Granular Spatio-Temporal Token Merging for Training-Free Acceleration of Video LLMs

Jeongseok Hyun, Sukjun Hwang, Su Ho Han +6

Video large language models (LLMs) achieve strong video understanding by leveraging a large number of spatio-temporal tokens, but suffer from quadratic computational scaling with t…

cs.LG2025

Dynamic Chunking for End-to-End Hierarchical Sequence Modeling

Sukjun Hwang, Brandon Wang, Albert Gu

Major progress on language models (LMs) in recent years has largely resulted from moving away from specialized models designed for specific tasks, to general models based on powerf…