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Back to zouchuhang/layoutnet

Open-source alternatives to LayoutNet

30 open-source projects similar to zouchuhang/layoutnet, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best LayoutNet alternative.

  • cyang0515/noncuboidroomCYang0515 的头像

    CYang0515/NonCuboidRoom

    116在 GitHub 上查看↗

    Learning to Reconstruct 3D Non-Cuboid Room Layout from a Single RGB Image

    Python
    在 GitHub 上查看↗116
  • rshivansh/omnilayoutrshivansh 的头像

    rshivansh/OmniLayout

    2在 GitHub 上查看↗

    This is the implementation of our CVPRW'21 paper " OmniLayout: Room Layout Reconstruction from Indoor Spherical Panoramas " accepted at the 2nd workshop on Omnidirectional Computer Vision.

    在 GitHub 上查看↗2
  • manycore-research/spatiallmmanycore-research 的头像

    manycore-research/SpatialLM

    4,596在 GitHub 上查看↗

    SpatialLM is a spatial modeling framework that uses large language models to transform monocular video and sensor data into structured indoor semantic maps. It functions as a system for indoor layout estimation and a point cloud semantic parser, converting raw geometric data into representations of architectural elements and object categories. The project aligns multi-modal sensor inputs with linguistic tokens, allowing a language model to serve as a reasoning engine for inferring room topology. It employs mechanisms to convert 3D point clouds and 2D image sequences into discrete tokens and s

    Pythonmllmpoint-cloudsscene-understanding
    在 GitHub 上查看↗4,596
  • zalandoresearch/fashion-mnistzalandoresearch 的头像

    zalandoresearch/fashion-mnist

    12,754在 GitHub 上查看↗

    This project is a computer vision benchmark and image classification dataset used to measure and compare the accuracy of machine learning models. It provides a standardized collection of labeled fashion product images and training data formatted to be compatible with the MNIST dataset structure. The dataset consists of fixed-dimension grayscale images and label-based category mappings, stored in a binary format. It includes pre-split training and testing sets and a static distribution to ensure consistent cross-model benchmarking. The repository supports image classification benchmarking and

    Pythonbenchmarkcomputer-visionconvolutional-neural-networks
    在 GitHub 上查看↗12,754

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  • akanazawa/cmrakanazawa 的头像

    akanazawa/cmr

    485在 GitHub 上查看↗

    Angjoo Kanazawa \ , Shubham Tulsiani \ , Alexei A. Efros, Jitendra Malik

    Python
    在 GitHub 上查看↗485
  • akanazawa/hmrakanazawa 的头像

    akanazawa/hmr

    1,665在 GitHub 上查看↗

    Project page for End-to-end Recovery of Human Shape and Pose

    Python
    在 GitHub 上查看↗1,665
  • agrimgupta92/sganagrimgupta92 的头像

    agrimgupta92/sgan

    912在 GitHub 上查看↗

    Code for "Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks", Gupta et al, CVPR 2018

    Python
    在 GitHub 上查看↗912
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    aimerykong/Recurrent-Pixel-Embedding-for-Instance-Grouping

    146在 GitHub 上查看↗

    CVPR2018 - pixel embedding & grouping for structured prediction, e.g., instance segmentation

    MATLAB
    在 GitHub 上查看↗146
  • alexsax/2d-3d-semanticsalexsax 的头像

    alexsax/2D-3D-Semantics

    532在 GitHub 上查看↗

    The 2D-3D-S dataset provides a variety of mutually registered modalities from 2D, 2.5D and 3D domains, with instance-level semantic and geometric annotations. It covers over 6,000 m2 collected in 6 large-scale indoor areas that originate from 3 different buildings. It contains over 70,000 RGB…

    C++
    在 GitHub 上查看↗532
  • alokwhitewolf/guided-attention-inference-networkalokwhitewolf 的头像

    alokwhitewolf/Guided-Attention-Inference-Network

    238在 GitHub 上查看↗

    Contains implementation of Guided Attention Inference Network (GAIN) presented in Tell Me Where to Look(CVPR 2018). This repository aims to apply GAIN on fcn8 architecture used for segmentation.

    Python
    在 GitHub 上查看↗238
  • alterzero/dbpn-pytorchalterzero 的头像

    alterzero/DBPN-Pytorch

    574在 GitHub 上查看↗

    The project is an official implement of our CVPR2018 paper "Deep Back-Projection Networks for Super-Resolution" (Winner of NTIRE2018 and PIRM2018)

    Python
    在 GitHub 上查看↗574
  • amlab-amsterdam/attentiondeepmilA

    AMLab-Amsterdam/AttentionDeepMIL

    0在 GitHub 上查看↗

    Attention-based Deep Multiple Instance Learning

    在 GitHub 上查看↗0
  • amusi/daily-paper-computer-visionamusi 的头像

    amusi/daily-paper-computer-vision

    6,768在 GitHub 上查看↗

    记录每天整理的计算机视觉/深度学习/机器学习相关方向的论文

    computer-visiondeep-learningface-detection
    在 GitHub 上查看↗6,768
  • anishathalye/obfuscated-gradientsanishathalye 的头像

    anishathalye/obfuscated-gradients

    907在 GitHub 上查看↗

    Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples

    Jupyter Notebook
    在 GitHub 上查看↗907
  • albertpumarola/ganimationalbertpumarola 的头像

    albertpumarola/GANimation

    1,984在 GitHub 上查看↗

    Official implementation of GANimation. In this work we introduce a novel GAN conditioning scheme based on Action Units (AU) annotations, which describe in a continuous manifold the anatomical facial movements defining a human expression. Our approach permits controlling the magnitude of…

    Python
    在 GitHub 上查看↗1,984
  • angeladai/scancompleteangeladai 的头像

    angeladai/ScanComplete

    271在 GitHub 上查看↗

    CVPR'18 ScanComplete: Large-Scale Scene Completion and Semantic Segmentation for 3D Scans

    Python
    在 GitHub 上查看↗271
  • art-programmer/planenetart-programmer 的头像

    art-programmer/PlaneNet

    422在 GitHub 上查看↗

    PlaneNet: Piece-wise Planar Reconstruction from a Single RGB Image

    Python
    在 GitHub 上查看↗422
  • arunmallya/packnetarunmallya 的头像

    arunmallya/packnet

    243在 GitHub 上查看↗

    Code for PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning

    Python
    在 GitHub 上查看↗243
  • arunmallya/piggybackarunmallya 的头像

    arunmallya/piggyback

    183在 GitHub 上查看↗

    Code for Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights

    Python
    在 GitHub 上查看↗183
  • assafshocher/zssrassafshocher 的头像

    assafshocher/ZSSR

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    "Zero-Shot" Super-Resolution using Deep Internal Learning

    Python
    在 GitHub 上查看↗421
  • azadis/mc-ganazadis 的头像

    azadis/MC-GAN

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    Multi-Content GAN for Few-Shot Font Style Transfer at CVPR 2018

    Python
    在 GitHub 上查看↗447
  • balakg/posewarp-cvpr2018balakg 的头像

    balakg/posewarp-cvpr2018

    194在 GitHub 上查看↗

    Code for our CVPR 2018 paper: "Synthesizing Images of Humans in Unseen Poses"

    Python
    在 GitHub 上查看↗194
  • bermanmaxim/lovaszsoftmaxbermanmaxim 的头像

    bermanmaxim/LovaszSoftmax

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    Maxim Berman, Amal Rannen Triki, Matthew B. Blaschko

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    在 GitHub 上查看↗1,412
  • brain-research/long-term-video-prediction-without-supervisionbrain-research 的头像

    brain-research/long-term-video-prediction-without-supervision

    89在 GitHub 上查看↗

    This is the implementation of Hierarchical Long-term Video Prediction without Supervision, to be published in ICML 2018.

    Python
    在 GitHub 上查看↗89
  • brain-research/realistic-ssl-evaluationbrain-research 的头像

    brain-research/realistic-ssl-evaluation

    459在 GitHub 上查看↗

    Open source release of the evaluation benchmark suite described in "Realistic Evaluation of Deep Semi-Supervised Learning Algorithms"

    Python
    在 GitHub 上查看↗459
  • bytedance/x-dynabytedance 的头像

    bytedance/X-Dyna

    269在 GitHub 上查看↗

    CVPR 2025 Highlight X-Dyna: Expressive Dynamic Human Image Animation

    Python
    在 GitHub 上查看↗269
  • byteflow-ai/tokenflowByteFlow-AI 的头像

    ByteFlow-AI/TokenFlow

    465在 GitHub 上查看↗

    CVPR 2025 🔥 Official impl. of "TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation".

    Python
    在 GitHub 上查看↗465
  • camel007/caffe-shufflenetcamel007 的头像

    camel007/Caffe-ShuffleNet

    159在 GitHub 上查看↗

    This is re-implementation of "ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices"

    C++
    在 GitHub 上查看↗159
  • angeladai/3dmvangeladai 的头像

    angeladai/3DMV

    213在 GitHub 上查看↗

    3DMV jointly combines RGB color and geometric information to perform 3D semantic segmentation of RGB-D scans. This work is based on our ECCV'18 paper, 3DMV: Joint 3D-Multi-View Prediction for 3D Semantic Scene Segmentation.

    Python
    在 GitHub 上查看↗213