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Princeton Vision & Learning Lab
59 posts
@PrincetonVL

Princeton Vision & Learning Lab

@PrincetonVL
pvl.cs.princeton.edu
Princeton, NJ
Joined March 2023
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  • @PrincetonVL
    Princeton Vision & Learning Lab
    @PrincetonVL
    Sep 2
    We’ve released InFlux++, our unified data suite for training and evaluating dynamic intrinsics prediction models. See below for more info, or visit us in person at #ECCV2026!
    @ErichLiang
    Erich Liang @ ECCV 2026
    @ErichLiang
    Sep 1
    Dynamic camera intrinsics often appear in robotics and 3D vision—yet training and evaluation data for predicting them from RGB is surprisingly rare. Introducing InFlux++: our new real-world benchmark and synthetic training dataset for dynamic intrinsics prediction. 🧵1/6
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  • @PrincetonVL
    Princeton Vision & Learning Lab
    @PrincetonVL
    Jul 8
    We've released a preview of Infinigen 2.0 - new high quality procedural materials and scenes with an efficient and controllable Python API. See below for info!
    @alex_raistrick
    Alexander Raistrick
    @alex_raistrick
    Jul 8
    1/ We've released Infinigen 2.0! Currently in preview. It creates indoor 3D scene files in 1min CPU time, and includes new and better materials --- all still fully procedural. Our new 2.0 design is highly efficient and allows easy control and recombination via Python APIs.
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  • @PrincetonVL
    Princeton Vision & Learning Lab
    @PrincetonVL
    Mar 31
    Stereo depth is highly useful for robots. Meet WAFT-Stereo: #1 on ETH3D (BP-0.5), Middlebury (RMSE), and KITTI (all metrics); 61% less zero-shot ETH3D BP-0.5 error; 1.8-6.7x faster than prior SOTA. Key idea: classify disparity into bins, then iterative high-res warping.🧵1/2
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  • @PrincetonVL
    Princeton Vision & Learning Lab
    @PrincetonVL
    Feb 10
    Meet WAFT (Warping-Alone Field Transforms), our new optical-flow estimator. #1 on public benchmarks (Sintel & Spring), 1.3-4.1x faster than leading methods, and 2x lower memory. Key idea: replace cost volumes with high-res feature-space warping. Code and paper:👇
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  • @PrincetonVL
    Princeton Vision & Learning Lab
    @PrincetonVL
    Dec 1, 2025
    Estimating camera intrinsics from video is key to 3D reconstruction, but most methods assume they’re fixed per video. What if the camera keeps zooming and refocusing? Meet InFlux, the first benchmark with per-frame ground truth for videos with dynamic intrinsics. 🧵1/5
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