HumanSplatHMR jointly refines 3D human poses and learns Gaussian Splatting avatars by backpropagating photometric, segmentation, and depth losses through a differentiable renderer to improve novel-view and novel-pose synthesis from in-the-wild video.
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HVG-3D uses a 3D-aware diffusion architecture with ControlNet to synthesize high-fidelity hand-object interaction videos from 3D control signals, achieving state-of-the-art spatial fidelity and temporal coherence on the TASTE-Rob dataset.
PercHead achieves state-of-the-art single-image 3D head reconstruction and editing by replacing low-level losses with a perceptual loss from DINOv2 and SAM 2.1 inside a Vision Transformer architecture.
SwiftPie enables one-step diffusion for fast, high-quality subject-driven image personalization comparable to slower multi-step methods.
citing papers explorer
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HumanSplatHMR: Closing the Loop Between Human Mesh Recovery and Gaussian Splatting Avatar
HumanSplatHMR jointly refines 3D human poses and learns Gaussian Splatting avatars by backpropagating photometric, segmentation, and depth losses through a differentiable renderer to improve novel-view and novel-pose synthesis from in-the-wild video.
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HVG-3D: Bridging Real and Simulation Domains for 3D-Conditional Hand-Object Interaction Video Synthesis
HVG-3D uses a 3D-aware diffusion architecture with ControlNet to synthesize high-fidelity hand-object interaction videos from 3D control signals, achieving state-of-the-art spatial fidelity and temporal coherence on the TASTE-Rob dataset.
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PercHead: Perceptual Head Model for Single-Image 3D Head Reconstruction & Editing
PercHead achieves state-of-the-art single-image 3D head reconstruction and editing by replacing low-level losses with a perceptual loss from DINOv2 and SAM 2.1 inside a Vision Transformer architecture.
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SwiftPie: Lightning-fast Subject-driven Image Personalization via One step Diffusion
SwiftPie enables one-step diffusion for fast, high-quality subject-driven image personalization comparable to slower multi-step methods.