4 citations · 7 across the 12 of their papers we have counts for
13 papers
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…
Decoding Children's Gait Behavior
Yifan Shen, Boyi Li, Meihuan Huang +12
We introduce a new problem domain for human action recognition: the fine-grained analysis of children's gait behaviors from standard RGB video. We specifically target the ambulator…
Evaluating Cognitive Age Alignment in Interactive AI Agents
Yifan Shen, Jiawen Zhang, Jian Xu +4
While agentic AI and its core multimodal large language models (MLLMs) have demonstrated remarkable promise in language and visual reasoning across domains ranging from daily life…
GRASP: Learning to Ground Social Reasoning in Multi-Person Non-Verbal Interactions
Junho Kim, Xu Cao, Houze Yang +6
Understanding social interactions requires reasoning over subtle non-verbal cues, yet current multimodal large language models (MLLMs) often fail to identify who interacts with who…
Generating Humanless Environment Walkthroughs from Egocentric Walking Tour Videos
Yujin Ham, Junho Kim, Vivek Boominathan +1
Egocentric "walking tour" videos provide a rich source of image data to develop rich and diverse visual models of environments around the world. However, the significant presence o…
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…
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…
DIP-R1: Deep Inspection and Perception with RL Looking Through and Understanding Complex Scenes
Sungjune Park, Hyunjun Kim, Junho Kim +2
MLLMs have demonstrated significant visual understanding capabilities, yet their fine-grained visual perception in complex real-world scenarios, such as densely crowded public area…
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…
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…
CODE: Contrasting Self-generated Description to Combat Hallucination in Large Multi-modal Models
Junho Kim, Hyunjun Kim, Yeonju Kim +1
Large Multi-modal Models (LMMs) have recently demonstrated remarkable abilities in visual context understanding and coherent response generation. However, alongside these advanceme…
What if...?: Thinking Counterfactual Keywords Helps to Mitigate Hallucination in Large Multi-modal Models
Junho Kim, Yeon Ju Kim, Yong Man Ro
This paper presents a way of enhancing the reliability of Large Multi-modal Models (LMMs) in addressing hallucination, where the models generate cross-modal inconsistent responses.…
Causal Unsupervised Semantic Segmentation
Junho Kim, Byung-Kwan Lee, Yong Man Ro
Unsupervised semantic segmentation aims to achieve high-quality semantic grouping without human-labeled annotations. With the advent of self-supervised pre-training, various framew…