Evidence Receipt. Related Resources.
Fast SAM 3D Body: Accelerating SAM 3D Body for Real-Time Full-Body Human Mesh Recovery
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Verification pending
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Page Freshness
Signal Canvas proof surface
Canonical route: /signal-canvas/fast-sam-3d-body-accelerating-sam-3d-body-for-real-time-full-body-human-mesh-recovery
- Proof freshness
- stale
- Proof status
- unverified
- Display score
- 8/10
- Last proof check
- 2026-04-02
- Score updated
- 2026-04-02
- Score fresh until
- 2026-05-02
- References
- 0
- Source count
- 0
- Coverage
- 17%
This page is showing the last landed evidence receipt and score bundle because the latest proof data is outside the freshness window.
Agent Handoff
Fast SAM 3D Body: Accelerating SAM 3D Body for Real-Time Full-Body Human Mesh Recovery
Canonical ID fast-sam-3d-body-accelerating-sam-3d-body-for-real-time-full-body-human-mesh-recovery | Route /signal-canvas/fast-sam-3d-body-accelerating-sam-3d-body-for-real-time-full-body-human-mesh-recovery
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/fast-sam-3d-body-accelerating-sam-3d-body-for-real-time-full-body-human-mesh-recoveryMCP example
{
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"query_text": "Summarize Fast SAM 3D Body: Accelerating SAM 3D Body for Real-Time Full-Body Human Mesh Recovery"
}
}source_context
{
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"mode": "paper",
"query": "Fast SAM 3D Body: Accelerating SAM 3D Body for Real-Time Full-Body Human Mesh Recovery",
"normalized_query": "2603.15603",
"route": "/signal-canvas/fast-sam-3d-body-accelerating-sam-3d-body-for-real-time-full-body-human-mesh-recovery",
"paper_ref": "fast-sam-3d-body-accelerating-sam-3d-body-for-real-time-full-body-human-mesh-recovery",
"topic_slug": null,
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}Preparing verified analysis
Dimensions overall score 8.0
GitHub Code Pulse
No public code linked for this paper yet.
Claim map
- Evidencepartial
Overall, our framework delivers up to a 10.9x end-to-end speedup while maintaining on-par reconstruction fidelity
ImplicationpartialThis is a direct quantitative result stated in the abstract.
Verificationpartialpartial
- Evidencepartial
We present Fast SAM 3D Body, a training-free acceleration framework that reformulates the 3DB inference pathway to achieve interactive rates.
ImplicationpartialThe title and abstract emphasize 'Fast' and 'Real-Time', and the abstract mentions achieving 'interactive rates'.
Verificationpartialpartial
- Evidencepartial
Moreover, to extract the joint-level kinematics (SMPL) compatible with existing humanoid control and policy learning frameworks, we replace the iterative mesh fitting with a direct feedforward mapping, accelerating this specific conversion by over 10,000x.
ImplicationpartialThis is a specific technical detail and a significant quantitative improvement mentioned in the abstract.
Verificationpartialpartial
- Evidencepartial
Overall, our framework delivers up to a 10.9x end-to-end speedup while maintaining on-par reconstruction fidelity, even surpassing 3DB on benchmarks such as LSPET.
ImplicationpartialThe abstract explicitly states this comparison and mentions surpassing on a specific benchmark.
Verificationpartialpartial
- Evidencepartial
We demonstrate its utility by deploying Fast SAM 3D Body in a vision-only teleoperation system that-unlike methods reliant on wearable IMUs-enables real-time humanoid control and the direct collection of manipulation policies from a single RGB stream.
ImplicationpartialThis is a demonstrated utility and application described in the abstract.
Verificationpartialpartial
- Evidencepartial
Proprietary acceleration techniques (architecture-aware pruning, parallelized feature extraction) and the direct feedforward mapping for SMPL conversion, which are hard to replicate without deep expertise in 3D human mesh recovery and transformer optimization.
ImplicationpartialThe 'moat_source' section identifies these techniques as proprietary and hard to replicate, indicating a market advantage.
Verificationpartialpartial
- Evidencepartial
Mid-market robotics integrators building teleoperation systems for industrial automation, such as companies deploying humanoid robots in warehouses for picking and packing tasks.
ImplicationpartialThe 'ideal_customer' section specifies this target market.
Verificationpartialpartial