Laurent Guigues — accepted AI-conference papers

2026

HAD: Hallucination-Aware Diffusion Priors for 3D Reconstruction

Xi Liu, Weiwei Sun, Zhou Ren, Chris Broaddus, Siyu Huang, Laurent Guigues

CVPR 2026

Diffusion priors have recently demonstrated strong capability in enhancing the quality of sparse-view 3D reconstruction by augmenting training views at novel viewpoints, but they inevitably introduce hallucinated content-- artifacts inconsistent with the input views -- into the final 3D model. To ad

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2021

TesseTrack: End-to-End Learnable Multi-Person Articulated 3D Pose Tracking

N Dinesh Reddy, Laurent Guigues, Leonid Pishchulin, Jayan Eledath, Srinivasa G. Narasimhan

CVPR 2021poster

We consider the task of 3D pose estimation and trackingof multiple people seen in an arbitrary number of camerafeeds. We propose TesseTrack, a novel top-down approachthat simultaneously reasons about multiple individuals' 3Dbody joint reconstructions and associations in space andtime in a single end…

Cited by 135 PDF ↗Scholar ↗