Vid2coach Top Work

: Vid2Coach analyzes how-to videos by combining narration and visual demonstrations to generate high-level steps and fine-grained demonstration details.

Vid2Coach isn’t just a voice‑over. The system ingests any standard how‑to video (e.g., a recipe or craft tutorial) and transforms it into a that:

: A standard instructional video (e.g., a cooking or repair tutorial) is processed by the Vid2Coach pipeline .

(* Lower numbers indicate less demand/effort/frustration, higher numbers indicate better performance)

: The system categorizes actions into punctual (quick tasks), iterative (repetitive motions), and durative (gradual changes) to provide context-aware responses and low-latency descriptions of user actions. vid2coach top

| | Vid2Coach (Research) | Traditional Video Coaching Software | |-------------|--------------------------|------------------------------------------| | Core Function | AI‑powered interactive assistant | Manual playback and analysis | | Instruction Extraction | Automatic (92% accuracy) | Manual annotation required | | Feedback | Real‑time, proactive | Post‑session, coach‑driven | | Hardware Integration | Wearable smart glasses | Desktop/mobile apps | | Target Users | Skill learners (originally BLV) | Sports coaches, PE teachers, athletes | | Key Strength | Autonomous guidance | Hands‑on control and customization |

Vid2Coach uses Large Multimodal Models (LMMs) to build structured guidance including: : What step to perform next.

Vid2Coach stands out by addressing the core limitations of existing video tutorials. It doesn’t just describe the video; it understands it, interprets it, and helps you perform it. Here is why it is becoming a top choice for accessibility: 1. Transformative AI for Accessibility (BLV)

For the working coach, time is the enemy. A typical in-person lesson yields maybe 4 to 6 repetitions of analysis. Remote video analysis usually means watching a 2-minute clip, typing a paragraph of text, and hoping the athlete understands. : Vid2Coach analyzes how-to videos by combining narration

is an AI-powered system designed to turn standard how-to videos into interactive, wearable "task assistants." Developed by researchers and presented at the ACM UIST Conference 2025, the system primarily uses commercial smart glasses

: Adapts to out-of-order execution, verifying individual step completion independently. Core Applications and Future Impact

Vid2Coach: How AI is Transforming Online How-To Videos into Smart Wearable Coaches

This isn't just about replacing vision—it's about strengthening independence with AI that truly understands the task at hand. It doesn’t just describe the video; it understands

In pilot studies, participants using Vid2Coach completed tasks with than their typical workflow. Vid2Coach: Transforming How-To Videos into Task Assistants

For more in-depth research on this topic, you can view the paper titled "Vid2Coach: Transforming How-To Videos into Task Assistants" on arXiv . If you'd like, I can:

, the research highlighted significant independence gains for users: Error Reduction : BLV participants in a study completed cooking tasks with 58.5% fewer errors compared to their typical methods. Mixed-Initiative Interaction

If you have been searching for the ultimate solution to bridge the gap between raw footage and actionable feedback, you have likely come across the term . But what exactly is it, and why is it quickly becoming the gold standard for athletes, coaches, and physical therapists worldwide?