4 citations · 4 across the 7 of their papers we have counts for
7 papers
Color When It Counts: Grayscale-Guided Online Triggering for Always-On Streaming Video Sensing
Weitong Cai, Hang Zhang, Yukai Huang +5
Always-on sensing is essential for next-generation edge/wearable AI systems, yet continuous high-fidelity RGB video capture remains prohibitively expensive for resource-constrained…
Egocentric Co-Pilot: Web-Native Smart-Glasses Agents for Assistive Egocentric AI
Sicheng Yang, Yukai Huang, Weitong Cai +8
What if accessing the web did not require a screen, a stable desk, or even free hands? For people navigating crowded cities, living with low vision, or experiencing cognitive overl…
EgoGraph: Temporal Knowledge Graph for Egocentric Video Understanding
Shitong Sun, Ke Han, Yukai Huang +2
Ultra-long egocentric videos spanning multiple days present significant challenges for video understanding. Existing approaches still rely on fragmented local processing and limite…
Optimizing Multimodal LLMs for Egocentric Video Understanding: A Solution for the HD-EPIC VQA Challenge
Sicheng Yang, Yukai Huang, Shitong Sun +4
Multimodal Large Language Models (MLLMs) struggle with complex video QA benchmarks like HD-EPIC VQA due to ambiguous queries/options, poor long-range temporal reasoning, and non-st…
Plug-and-Play Clarifier: A Zero-Shot Multimodal Framework for Egocentric Intent Disambiguation
Sicheng Yang, Yukai Huang, Weitong Cai +6
The performance of egocentric AI agents is fundamentally limited by multimodal intent ambiguity. This challenge arises from a combination of underspecified language, imperfect visu…
MLLM as Video Narrator: Mitigating Modality Imbalance in Video Moment Retrieval
Weitong Cai, Jiabo Huang, Shaogang Gong +2
Video Moment Retrieval (VMR) aims to localize a specific temporal segment within an untrimmed long video given a natural language query. Existing methods often suffer from inadequa…
Relax Image-Specific Prompt Requirement in SAM: A Single Generic Prompt for Segmenting Camouflaged Objects
Jian Hu, Jiayi Lin, Weitong Cai +1
Camouflaged object detection (COD) approaches heavily rely on pixel-level annotated datasets. Weakly-supervised COD (WSCOD) approaches use sparse annotations like scribbles or poin…