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Machine Heart
Machine Heart
Apr 23, 2026 · Artificial Intelligence

UniLS: End-to-End Audio-Driven Framework Eliminates the ‘Poker Face’ in Digital Human Dialogue

UniLS, the first end‑to‑end audio‑driven framework that jointly generates speaking and listening facial motions for digital humans, achieves state‑of‑the‑art speaking accuracy, improves listening naturalness by 44.1 %, and runs at over 500 FPS, as demonstrated on the CVPR 2026‑accepted paper with extensive quantitative and user studies.

CVPR 2026audio-driven animationdigital humans
0 likes · 9 min read
UniLS: End-to-End Audio-Driven Framework Eliminates the ‘Poker Face’ in Digital Human Dialogue
Machine Heart
Machine Heart
Apr 12, 2026 · Artificial Intelligence

CVPR 2026 WorldArena Challenge Launches with Amap’s Open‑Source High‑Performance World Model Baseline

The CVPR 2026 WorldArena Challenge, organized by top academic institutions and Amap, introduces a new evaluation framework that tests video world models for physical realism and functional utility, while Amap releases its high‑performance ABot‑PhysWorld model and benchmark scores that set a new state‑of‑the‑art.

ABot-PhysWorldCVPR 2026Physical Consistency
0 likes · 9 min read
CVPR 2026 WorldArena Challenge Launches with Amap’s Open‑Source High‑Performance World Model Baseline
Machine Heart
Machine Heart
Apr 12, 2026 · Artificial Intelligence

Breaking Camera Dependence: M4Human Advances Millimeter-Wave Human Perception to New Levels

The M4Human paper introduces a large‑scale multimodal mmWave radar benchmark for high‑fidelity human mesh reconstruction, detailing its data collection pipeline, annotation quality, benchmark splits, a raw‑radar‑tensor baseline (RT‑Mesh), and extensive experiments that show radar’s privacy‑friendly robustness and complementary strength to visual sensors.

CVPR 2026M4HumanRF dataset
0 likes · 13 min read
Breaking Camera Dependence: M4Human Advances Millimeter-Wave Human Perception to New Levels
Machine Heart
Machine Heart
Apr 10, 2026 · Artificial Intelligence

Ant AI Wins CVPR 2026 Challenge: A Powerful Countermeasure Against Deepfake Abuse

Amid rising deep‑fake misuse in entertainment, Ant Group’s AI Security Lab won the CVPR 2026 NTIRE Robust AIGC Image Detection challenge with a ROC AUC of 0.9723, presenting a DINOv3‑based robust detection framework, extensive multi‑source data, and novel augmentation and optimization techniques to combat AI‑generated abuse.

AIGCCVPR 2026DINOv3
0 likes · 10 min read
Ant AI Wins CVPR 2026 Challenge: A Powerful Countermeasure Against Deepfake Abuse
Machine Heart
Machine Heart
Apr 8, 2026 · Artificial Intelligence

From a Single Image to a Physically Realistic 4D Video in One Minute

PhysGM, a CVPR 2026 paper by Beijing Institute of Technology and Li Auto, transforms a single static image into a high‑fidelity 4D video that obeys real‑world physics in under a minute, using a dual‑decoder transformer, DPO alignment, and a newly built 50k‑item PhysAssets dataset, outperforming prior methods in speed and quality.

3D Gaussian SplattingCVPR 2026Direct Preference Optimization
0 likes · 7 min read
From a Single Image to a Physically Realistic 4D Video in One Minute
vivo Internet Technology
vivo Internet Technology
Apr 1, 2026 · Artificial Intelligence

Why Fixed CFG Fails and How Time‑Adaptive C²FG Boosts Diffusion Image Generation

This article introduces C²FG, a training‑free, plug‑and‑play time‑adaptive exponential control function that replaces the fixed classifier‑free guidance scale, theoretically justifies its superiority with score discrepancy bounds, and demonstrates significant FID and IS improvements across multiple diffusion architectures on ImageNet.

CVPR 2026Classifier-Free GuidanceDiffusion Models
0 likes · 7 min read
Why Fixed CFG Fails and How Time‑Adaptive C²FG Boosts Diffusion Image Generation
Machine Learning Algorithms & Natural Language Processing
Machine Learning Algorithms & Natural Language Processing
Mar 22, 2026 · Artificial Intelligence

NS-Diff: Adding a Physics Engine to Diffusion Models for Fluid and Rigid‑Body Dynamics

The CVPR 2026 paper introduces NS‑Diff, a physics‑guided video diffusion framework that combines a noise‑robust dynamics detector, a physical‑condition latent injection module, and reinforcement‑learning optimization to reduce jerk error by 43 % and fluid divergence by 33 %, achieving superior physical realism and visual quality across multiple benchmarks.

CVPR 2026NS‑DiffNavier-Stokes
0 likes · 13 min read
NS-Diff: Adding a Physics Engine to Diffusion Models for Fluid and Rigid‑Body Dynamics
AIWalker
AIWalker
Mar 12, 2026 · Artificial Intelligence

BeautyGRPO: RL‑Driven Realistic Portrait Retouching Ends Over‑Beautification (CVPR 2026)

The paper introduces BeautyGRPO, a reinforcement‑learning framework that combines a fine‑grained preference dataset (FRPref‑10K) with Dynamic Path Guidance to balance aesthetic enhancement and high‑fidelity preservation in portrait retouching, achieving superior metrics and user preference over existing SFT and RL models.

AI aestheticsCVPR 2026dynamic path guidance
0 likes · 11 min read
BeautyGRPO: RL‑Driven Realistic Portrait Retouching Ends Over‑Beautification (CVPR 2026)