Hugging Face Trending Papers

From Sign Language Generation to Humanoid Execution: Vision-Language Guided Retargeting with Collision Mitigation

Recent sign language generation (SLG) systems increasingly output dense 3D body representations, which better preserve full-body kinematics and geometry for downstream embodiment on humanoid robots. However, these generated motions frequently exhibit self-intersections such as hand-hand and hand-torso penetration.

arXiv AI
Sep 16

SafeFlow: Real-Time Text-Driven Humanoid Whole-Body Control via Physics-Guided Rectified Flow and Selective Safety Gating

SafeFlow is a real‑time, text‑driven humanoid control framework that blends physics‑guided motion generation with a three‑stage safety gate. It uses Physics‑Guided Rectified Flow Matching in a VAE latent space to produce physically executable trajectories, accelerates sampling with Reflow, and filters unsafe outputs via semantic OOD detection, directional sensitivity checks, and hard kinematic constraints before handing them to a motion‑tracking controller. Experiments on the Unitree G1 show that SafeFlow achieves higher success rates, better physical compliance, and faster inference than diffusion‑ and retargeting‑based baselines while maintaining motion diversity.

By Hanbyel Cho, Sang-Hun Kim, Jeonguk Kang, Donghan Koo
arXiv Computer Vision
Aug 31

SignRR: Retrieve and Refine Real Motion for Sign Language Production

SignRR is a new sign language production framework that combines retrieval of real sign motion segments with a learned refinement step to produce globally coherent signing sequences. It starts from a dictionary of authentic sign segments and refines them using a part-aware Residual VQ‑VAE, preserving fine hand articulation while handling temporal length differences in latent space. Experiments on PHOENIX14T and CSL‑Daily demonstrate state‑of‑the‑art back‑translation performance and competitive pose quality.

By Fidel Omar Tito Cruz, Angie Sanchez Marquina, Summy Farfan, Gissella Bejarano
Hugging Face Trending Papers
Sep 3

BRIDGE: An Open-Source Humanoid Platform via Morphology-Control Co-Design for Physical AI

The paper presents BRIDGE, an open‑source 88 cm tall humanoid robot designed through a data‑driven morphology‑control co‑design framework that aligns robot shape with human‑like movement. It introduces a new metric combining kinematic retargeting fidelity and dynamic tracking performance to evaluate morphological fidelity, achieving state‑of‑the‑art results against baseline humanoids. The released platform, along with its control policy, demonstrates superior human motion capture, robust balance, and dynamic maneuvers, with supporting videos and code available online.

arXiv Computer Vision
Sep 15

SignMimic: Robust High-Quality Sign Language Motion Generation via Human-Shape-Oblivious Pose Transfer Guidance

arXiv:2609.14122v1 Announce Type: new Abstract: We study the challenge of sign language video mimicking: given a driving video and a single reference frame, synthesize a video where the target signer...

By Zhewen He (New York University Abu Dhabi), Junyi Yu (New York University Abu Dhabi), Haomian Huang (New York University Abu Dhabi), Zhenhua Li (ChatSign Technology), Yi Fang (New York University Abu Dhabi, ChatSign Technology)