2 citations · 3 across the 9 of their papers we have counts for
9 papers
Self-Refining Video Sampling
Sangwon Jang, Taekyung Ki, Jaehyeong Jo +3
Modern video generators still struggle with complex physical dynamics, often falling short of physical realism. Existing approaches address this using external verifiers or additio…
Avatar Forcing: Real-Time Interactive Head Avatar Generation for Natural Conversation
Taekyung Ki, Sangwon Jang, Jaehyeong Jo +2
Talking head generation creates lifelike avatars from static portraits for virtual communication and content creation. However, current models do not yet convey the feeling of trul…
WorldMM: Dynamic Multimodal Memory Agent for Long Video Reasoning
Woongyeong Yeo, Kangsan Kim, Jaehong Yoon +1
Recent advances in video large language models have demonstrated strong capabilities in understanding short clips. However, scaling them to hours- or days-long videos remains highl…
Frame Guidance: Training-Free Guidance for Frame-Level Control in Video Diffusion Models
Sangwon Jang, Taekyung Ki, Jaehyeong Jo +4
Advancements in diffusion models have significantly improved video quality, directing attention to fine-grained controllability. However, many existing methods depend on fine-tunin…
Concept-skill Transferability-based Data Selection for Large Vision-Language Models
Jaewoo Lee, Boyang Li, Sung Ju Hwang
Instruction tuning, or supervised finetuning on extensive task-specific data, is necessary for Large Vision-Language Models (LVLMs) to generalize well across a broad range of visio…
BECoTTA: Input-dependent Online Blending of Experts for Continual Test-time Adaptation
Daeun Lee, Jaehong Yoon, Sung Ju Hwang
Continual Test Time Adaptation (CTTA) is required to adapt efficiently to continuous unseen domains while retaining previously learned knowledge. However, despite the progress of C…
Continual Learning: Forget-free Winning Subnetworks for Video Representations
Haeyong Kang, Jaehong Yoon, Sung Ju Hwang +1
Inspired by the Lottery Ticket Hypothesis (LTH), which highlights the existence of efficient subnetworks within larger, dense networks, a high-performing Winning Subnetwork (WSN) i…
Carpe Diem: On the Evaluation of World Knowledge in Lifelong Language Models
Yujin Kim, Jaehong Yoon, Seonghyeon Ye +4
The dynamic nature of knowledge in an ever-changing world presents challenges for language models trained on static data; the model in the real world often requires not only acquir…
STELLA: Continual Audio-Video Pre-training with Spatio-Temporal Localized Alignment
Jaewoo Lee, Jaehong Yoon, Wonjae Kim +2
Continuously learning a variety of audio-video semantics over time is crucial for audio-related reasoning tasks in our ever-evolving world. However, this is a nontrivial problem an…