activity
20242026
most citedContextMRI: Enhancing Compressed Sensing MRI through Metadata Conditioning

2 citations · 2 across the 6 of their papers we have counts for

collaborators

9 papers

cs.CV2026

Future Video Generation Better Aligns with the Human Visual Cortex than Observed Video

Chang-Bae Bang, Hyungjin Chung, Byung-Hoon Kim

Studying the alignment between the internal representations of vision models and the responses of the visual cortex to the same observed visual stimuli has enabled us to better und…

cs.CV2026

FlashRender: Few-Step Generative Rendering via Camera-Controlled Video MeanFlow

Byeongjun Park, Byung-Hoon Kim, Hyungjin Chung

We present FlashRender, a few-step generative rendering framework that retakes a source video along a target camera trajectory in seconds. We identify sampling-step-dependent camer…

cs.CV2025

ReDirector: Creating Any-Length Video Retakes with Rotary Camera Encoding

Byeongjun Park, Byung-Hoon Kim, Hyungjin Chung +1

We present ReDirector, a novel camera-controlled video retake generation method for dynamically captured variable-length videos. In particular, we rectify a common misuse of RoPE i…

cs.CV2025

Generating Human Motion Videos using a Cascaded Text-to-Video Framework

Hyelin Nam, Hyojun Go, Byeongjun Park +2

Human video generation is becoming an increasingly important task with broad applications in graphics, entertainment, and embodied AI. Despite the rapid progress of video diffusion…

cs.CV2025

Video Parallel Scaling: Aggregating Diverse Frame Subsets for VideoLLMs

Hyungjin Chung, Hyelin Nam, Jiyeon Kim +6

Video Large Language Models (VideoLLMs) face a critical bottleneck: increasing the number of input frames to capture fine-grained temporal detail leads to prohibitive computational…

cs.CV2025

VideoRFSplat: Direct Scene-Level Text-to-3D Gaussian Splatting Generation with Flexible Pose and Multi-View Joint Modeling

Hyojun Go, Byeongjun Park, Hyelin Nam +3

We propose VideoRFSplat, a direct text-to-3D model leveraging a video generation model to generate realistic 3D Gaussian Splatting (3DGS) for unbounded real-world scenes. To genera…

cs.CV2025

SteerX: Creating Any Camera-Free 3D and 4D Scenes with Geometric Steering

Byeongjun Park, Hyojun Go, Hyelin Nam +3

Recent progress in 3D/4D scene generation emphasizes the importance of physical alignment throughout video generation and scene reconstruction. However, existing methods improve th…

cs.CV2025★ 2 cited

ContextMRI: Enhancing Compressed Sensing MRI through Metadata Conditioning

Hyungjin Chung, Dohun Lee, Zihui Wu +3

Compressed sensing MRI seeks to accelerate MRI acquisition processes by sampling fewer k-space measurements and then reconstructing the missing data algorithmically. The success of…

cs.CV2024

CapeLLM: Support-Free Category-Agnostic Pose Estimation with Multimodal Large Language Models

Junho Kim, Hyungjin Chung, Byung-Hoon Kim

Category-agnostic pose estimation (CAPE) has traditionally relied on support images with annotated keypoints, a process that is often cumbersome and may fail to fully capture the n…