activity
20242026
most citedLook Every Frame All at Once: Video-Mamba for Efficient Long-form Video Understanding with Multi-Axis Gradient Checkpointing

1 citations · 1 across the 4 of their papers we have counts for

collaborators
Showing cs.CVShow all

5 papers · 1 filter

cs.CV2026

PRISM: Predictive Recomposition via Semantic Latent Decomposition for View-invariant Video Representation Learning

Youngchae Chee, Hosu Lee, Sungjune Park +2

Cross-view video representation learning aims to capture viewpoint-invariant action semantics despite substantial appearance changes across egocentric and exocentric videos. Howeve…

cs.CV2026

STRIDE: When to Speak Meets Sequence Denoising for Streaming Video Understanding

Junho Kim, Hosu Lee, James M. Rehg +2

Recent progress in video large language models (Video-LLMs) has enabled strong offline reasoning over long and complex videos. However, real-world deployments increasingly require…

cs.CV2025

ReFoCUS: Reinforcement-guided Frame Optimization for Contextual Understanding

Hosu Lee, Junho Kim, Hyunjun Kim +1

Recent progress in Large Multi-modal Models (LMMs) has enabled effective vision-language reasoning, yet the ability to video understanding remains constrained by suboptimal frame s…

cs.CV20241 cited

Look Every Frame All at Once: Video-Mamba for Efficient Long-form Video Understanding with Multi-Axis Gradient Checkpointing

Hosu Lee, Junho Kim, Hyunjun Kim +1

With the growing scale and complexity of video data, efficiently processing long video sequences poses significant challenges due to the quadratic increase in memory and computatio…

cs.CV2024

SALOVA: Segment-Augmented Long Video Assistant for Targeted Retrieval and Routing in Long-Form Video Analysis

Junho Kim, Hyunjun Kim, Hosu Lee +1

Despite advances in Large Multi-modal Models, applying them to long and untrimmed video content remains challenging due to limitations in context length and substantial memory over…