most citedGestura: A LVLM-Powered System Bridging Motion and Semantics for Real-Time Free-Form Gesture Understanding

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cs.CV20251 cited

Gestura: A LVLM-Powered System Bridging Motion and Semantics for Real-Time Free-Form Gesture Understanding

Zhuoming Li, Aitong Liu, Mengxi Jia +5

Free-form gesture understanding is highly appealing for human-computer interaction, as it liberates users from the constraints of predefined gesture categories. However, the sole e…

cs.CV2025

TeleEgo: Benchmarking Egocentric AI Assistants in the Wild

Jiaqi Yan, Ruilong Ren, Jingren Liu +13

Egocentric AI assistants in real-world settings must process multi-modal inputs (video, audio, text), respond in real time, and retain evolving long-term memory. However, existing…

cs.CV2025

Mixture of Noise for Pre-Trained Model-Based Class-Incremental Learning

Kai Jiang, Zhengyan Shi, Dell Zhang +2

Class Incremental Learning (CIL) aims to continuously learn new categories while retaining the knowledge of old ones. Pre-trained models (PTMs) show promising capabilities in CIL.…

cs.CV20251 cited

Infinite Video Understanding

Dell Zhang, Xiangyu Chen, Jixiang Luo +6

The rapid advancements in Large Language Models (LLMs) and their multimodal extensions (MLLMs) have ushered in remarkable progress in video understanding. However, a fundamental ch…

cs.CV2025

Decoupling the Image Perception and Multimodal Reasoning for Reasoning Segmentation with Digital Twin Representations

Yizhen Li, Dell Zhang, Xuelong Li +1

Reasoning Segmentation (RS) is a multimodal vision-text task that requires segmenting objects based on implicit text queries, demanding both precise visual perception and vision-te…

cs.CV2025

SmartFreeEdit: Mask-Free Spatial-Aware Image Editing with Complex Instruction Understanding

Qianqian Sun, Jixiang Luo, Dell Zhang +1

Recent advancements in image editing have utilized large-scale multimodal models to enable intuitive, natural instruction-driven interactions. However, conventional methods still f…