RIFE: Real-Time Intermediate Flow Estimation for Video Frame Interpolation

Overview

RIFE

RIFE: Real-Time Intermediate Flow Estimation for Video Frame Interpolation

Ported from https://github.com/hzwer/arXiv2020-RIFE

Dependencies

  • NumPy
  • PyTorch, preferably with CUDA. Note that torchvision and torchaudio are not required and hence can be omitted from the command.
  • VapourSynth

Installation

pip install --upgrade vsrife

Usage

from vsrife import RIFE

ret = RIFE(clip)

See __init__.py for the description of the parameters.

Comments
  • Getting Error when interpolating

    Getting Error when interpolating

        model.load_model(os.path.join(os.path.dirname(__file__), model_dir), -1)
      File "C:\Users\\AppData\Local\Programs\Python\Python39\lib\site-packages\vsrife\RIFE_HDv2.py", line 164, in load_model
        convert(torch.load('{}/flownet.pkl'.format(path), map_location=self.torch_device)))
      File "C:\Users\\AppData\Local\Programs\Python\Python39\lib\site-packages\torch\serialization.py", line 608, in load
        return _legacy_load(opened_file, map_location, pickle_module, **pickle_load_args)
      File "C:\Users\\AppData\Local\Programs\Python\Python39\lib\site-packages\torch\serialization.py", line 777, in _legacy_load
        magic_number = pickle_module.load(f, **pickle_load_args)
    EOFError: Ran out of input  ```
    
    Source file is a 720p 30fps mp4, loaded into VS through Lsmash source, set the format to RGBS. Nothing else
    System specs are R7 3700x, 32GB of ram and a RTX 3060
    
    
    opened by banjaminicc 4
  • Small feature request for RIFEv4: target fps as alternative to multiplier

    Small feature request for RIFEv4: target fps as alternative to multiplier

    I would it be possible to allow setting a target fps instead of a multiplier when using RIFEv4? When going from for example 23.976 (24000/1001) to 60 fps, having to use (60 * 1001 / 24000 =) 2,5025 is kind of annoying. ;) I know could write a wrapper arount the rife.RIFE but I suspect depending on the resulting float it would be more accurate if this was done inside the filter.

    opened by Selur 3
  • vs-rife + latest vs-dpir don't work

    vs-rife + latest vs-dpir don't work

    When using just vs-rife:

    # Imports
    import vapoursynth as vs
    # getting Vapoursynth core
    core = vs.core
    # Loading Plugins
    core.std.LoadPlugin(path="i:/Hybrid/64bit/vsfilters/MiscFilter/MiscFilters/MiscFilters.dll")
    core.std.LoadPlugin(path="i:/Hybrid/64bit/vsfilters/DeinterlaceFilter/TIVTC/libtivtc.dll")
    core.std.LoadPlugin(path="i:/Hybrid/64bit/vsfilters/SourceFilter/d2vSource/d2vsource.dll")
    # source: 'C:\Users\Selur\Desktop\VTS_01_1.VOB'
    # current color space: YUV420P8, bit depth: 8, resolution: 720x480, fps: 29.97, color matrix: 470bg, yuv luminance scale: limited, scanorder: telecine
    # Loading C:\Users\Selur\Desktop\VTS_01_1.VOB using D2VSource
    clip = core.d2v.Source(input="E:/Temp/vob_941fdaaeda22090766694391cc4281d5_853323747.d2v")
    # Setting color matrix to 470bg.
    clip = core.std.SetFrameProps(clip, _Matrix=5)
    clip = clip if not core.text.FrameProps(clip,'_Transfer') else core.std.SetFrameProps(clip, _Transfer=5)
    clip = clip if not core.text.FrameProps(clip,'_Primaries') else core.std.SetFrameProps(clip, _Primaries=5)
    # Setting color range to TV (limited) range.
    clip = core.std.SetFrameProp(clip=clip, prop="_ColorRange", intval=1)
    # making sure frame rate is set to 29.970
    clip = core.std.AssumeFPS(clip=clip, fpsnum=30000, fpsden=1001)
    # Deinterlacing using TIVTC
    clip = core.tivtc.TFM(clip=clip)
    clip = core.tivtc.TDecimate(clip=clip, mode=7, rate=10, dupThresh=0.04, vidThresh=3.50, sceneThresh=15.00)# new fps: 10
    # make sure content is preceived as frame based
    clip = core.std.SetFieldBased(clip, 0)
    clip = core.misc.SCDetect(clip=clip,threshold=0.150)
    from vsrife import RIFE
    # adjusting color space from YUV420P8 to RGBS for VsTorchRIFE
    clip = core.resize.Bicubic(clip=clip, format=vs.RGBS, matrix_in_s="470bg", range_s="limited")
    # adjusting frame count&rate with RIFE (torch)
    clip = RIFE(clip, multi=3, device_type='cuda', device_index=0) # new fps: 20
    # adjusting output color from: RGBS to YUV420P8 for x264Model
    clip = core.resize.Bicubic(clip=clip, format=vs.YUV420P8, matrix_s="470bg", range_s="limited")
    # set output frame rate to 30.000fps
    clip = core.std.AssumeFPS(clip=clip, fpsnum=30, fpsden=1)
    # Output
    clip.set_output()
    

    everything works. But when I add latest vs-dpir:

    # Imports
    import vapoursynth as vs
    # getting Vapoursynth core
    core = vs.core
    import os
    import site
    # Import libraries for onnxruntime
    from ctypes import WinDLL
    path = site.getsitepackages()[0]+'/onnxruntime_dlls/'
    WinDLL(path+'cublas64_11.dll')
    WinDLL(path+'cudart64_110.dll')
    WinDLL(path+'cudnn64_8.dll')
    WinDLL(path+'cudnn_cnn_infer64_8.dll')
    WinDLL(path+'cudnn_ops_infer64_8.dll')
    WinDLL(path+'cufft64_10.dll')
    WinDLL(path+'cufftw64_10.dll')
    WinDLL(path+'nvinfer.dll')
    WinDLL(path+'nvinfer_plugin.dll')
    WinDLL(path+'nvparsers.dll')
    WinDLL(path+'nvonnxparser.dll')
    # Loading Plugins
    core.std.LoadPlugin(path="i:/Hybrid/64bit/vsfilters/MiscFilter/MiscFilters/MiscFilters.dll")
    core.std.LoadPlugin(path="i:/Hybrid/64bit/vsfilters/DeinterlaceFilter/TIVTC/libtivtc.dll")
    core.std.LoadPlugin(path="i:/Hybrid/64bit/vsfilters/SourceFilter/d2vSource/d2vsource.dll")
    # source: 'C:\Users\Selur\Desktop\VTS_01_1.VOB'
    # current color space: YUV420P8, bit depth: 8, resolution: 720x480, fps: 29.97, color matrix: 470bg, yuv luminance scale: limited, scanorder: telecine
    # Loading C:\Users\Selur\Desktop\VTS_01_1.VOB using D2VSource
    clip = core.d2v.Source(input="E:/Temp/vob_941fdaaeda22090766694391cc4281d5_853323747.d2v")
    # Setting color matrix to 470bg.
    clip = core.std.SetFrameProps(clip, _Matrix=5)
    clip = clip if not core.text.FrameProps(clip,'_Transfer') else core.std.SetFrameProps(clip, _Transfer=5)
    clip = clip if not core.text.FrameProps(clip,'_Primaries') else core.std.SetFrameProps(clip, _Primaries=5)
    # Setting color range to TV (limited) range.
    clip = core.std.SetFrameProp(clip=clip, prop="_ColorRange", intval=1)
    # making sure frame rate is set to 29.970
    clip = core.std.AssumeFPS(clip=clip, fpsnum=30000, fpsden=1001)
    # Deinterlacing using TIVTC
    clip = core.tivtc.TFM(clip=clip)
    clip = core.tivtc.TDecimate(clip=clip, mode=7, rate=10, dupThresh=0.04, vidThresh=3.50, sceneThresh=15.00)# new fps: 10
    # make sure content is preceived as frame based
    clip = core.std.SetFieldBased(clip, 0)
    from vsdpir import DPIR
    # adjusting color space from YUV420P8 to RGBS for vsDPIRDenoise
    clip = core.resize.Bicubic(clip=clip, format=vs.RGBS, matrix_in_s="470bg", range_s="limited")
    # denoising using DPIRDenoise
    clip = DPIR(clip=clip, strength=15.000, task="denoise", provider=1, device_id=0)
    clip = core.resize.Bicubic(clip=clip, format=vs.YUV444P16, matrix_s="470bg", range_s="limited")
    clip = core.misc.SCDetect(clip=clip,threshold=0.150)
    from vsrife import RIFE
    # adjusting color space from YUV444P16 to RGBS for VsTorchRIFE
    clip = core.resize.Bicubic(clip=clip, format=vs.RGBS, matrix_in_s="470bg", range_s="limited")
    # adjusting frame count&rate with RIFE (torch)
    clip = RIFE(clip, multi=3, device_type='cuda', device_index=0) # new fps: 20
    # adjusting output color from: RGBS to YUV420P8 for x264Model
    clip = core.resize.Bicubic(clip=clip, format=vs.YUV420P8, matrix_s="470bg", range_s="limited")
    # set output frame rate to 30.000fps
    clip = core.std.AssumeFPS(clip=clip, fpsnum=30, fpsden=1)
    # Output
    clip.set_output()
    

    I get:

    Python exception: [WinError 127] Die angegebene Prozedur wurde nicht gefunden. Error loading "I:\Hybrid\64bit\Vapoursynth\Lib/site-packages\torch\lib\cudnn_cnn_train64_8.dll" or one of its dependencies.
    

    Using just vs-dpir:

    # Imports
    import vapoursynth as vs
    # getting Vapoursynth core
    core = vs.core
    import os
    import site
    # Import libraries for onnxruntime
    from ctypes import WinDLL
    path = site.getsitepackages()[0]+'/onnxruntime_dlls/'
    WinDLL(path+'cublas64_11.dll')
    WinDLL(path+'cudart64_110.dll')
    WinDLL(path+'cudnn64_8.dll')
    WinDLL(path+'cudnn_cnn_infer64_8.dll')
    WinDLL(path+'cudnn_ops_infer64_8.dll')
    WinDLL(path+'cufft64_10.dll')
    WinDLL(path+'cufftw64_10.dll')
    WinDLL(path+'nvinfer.dll')
    WinDLL(path+'nvinfer_plugin.dll')
    WinDLL(path+'nvparsers.dll')
    WinDLL(path+'nvonnxparser.dll')
    # Loading Plugins
    core.std.LoadPlugin(path="i:/Hybrid/64bit/vsfilters/DeinterlaceFilter/TIVTC/libtivtc.dll")
    core.std.LoadPlugin(path="i:/Hybrid/64bit/vsfilters/SourceFilter/d2vSource/d2vsource.dll")
    # source: 'C:\Users\Selur\Desktop\VTS_01_1.VOB'
    # current color space: YUV420P8, bit depth: 8, resolution: 720x480, fps: 29.97, color matrix: 470bg, yuv luminance scale: limited, scanorder: telecine
    # Loading C:\Users\Selur\Desktop\VTS_01_1.VOB using D2VSource
    clip = core.d2v.Source(input="E:/Temp/vob_941fdaaeda22090766694391cc4281d5_853323747.d2v")
    # Setting color matrix to 470bg.
    clip = core.std.SetFrameProps(clip, _Matrix=5)
    clip = clip if not core.text.FrameProps(clip,'_Transfer') else core.std.SetFrameProps(clip, _Transfer=5)
    clip = clip if not core.text.FrameProps(clip,'_Primaries') else core.std.SetFrameProps(clip, _Primaries=5)
    # Setting color range to TV (limited) range.
    clip = core.std.SetFrameProp(clip=clip, prop="_ColorRange", intval=1)
    # making sure frame rate is set to 29.970
    clip = core.std.AssumeFPS(clip=clip, fpsnum=30000, fpsden=1001)
    # Deinterlacing using TIVTC
    clip = core.tivtc.TFM(clip=clip)
    clip = core.tivtc.TDecimate(clip=clip, mode=7, rate=10, dupThresh=0.04, vidThresh=3.50, sceneThresh=15.00)# new fps: 10
    # make sure content is preceived as frame based
    clip = core.std.SetFieldBased(clip, 0)
    from vsdpir import DPIR
    # adjusting color space from YUV420P8 to RGBS for vsDPIRDenoise
    clip = core.resize.Bicubic(clip=clip, format=vs.RGBS, matrix_in_s="470bg", range_s="limited")
    # denoising using DPIRDenoise
    clip = DPIR(clip=clip, strength=15.000, task="denoise", provider=1, device_id=0)
    # adjusting output color from: RGBS to YUV420P8 for x264Model
    clip = core.resize.Bicubic(clip=clip, format=vs.YUV420P8, matrix_s="470bg", range_s="limited")
    # set output frame rate to 10.000fps
    clip = core.std.AssumeFPS(clip=clip, fpsnum=10, fpsden=1)
    # Output
    clip.set_output()
    

    works fine.

    -> do you have an idea how I could fix this?

    opened by Selur 3
  • half the image is broken when using 4k content

    half the image is broken when using 4k content

    I get a broken output (see attachment), when using:

    # Imports
    import vapoursynth as vs
    # getting Vapoursynth core
    core = vs.core
    # Loading Plugins
    core.std.LoadPlugin(path="i:/Hybrid/64bit/vsfilters/MiscFilter/MiscFilters/MiscFilters.dll")
    core.std.LoadPlugin(path="i:/Hybrid/64bit/vsfilters/SourceFilter/LSmashSource/vslsmashsource.dll")
    # source: 'G:\TestClips&Co\files\MPEG-4 H.264\4k\Back to the Future (1985) 4k 10bit - 0.10.35-0.11.35.mkv'
    # current color space: YUV420P10, bit depth: 10, resolution: 3840x2076, fps: 23.976, color matrix: 2020ncl, yuv luminance scale: limited, scanorder: progressive
    # Loading G:\TestClips&Co\files\MPEG-4 H.264\4k\Back to the Future (1985) 4k 10bit - 0.10.35-0.11.35.mkv using LWLibavSource
    clip = core.lsmas.LWLibavSource(source="G:/TestClips&Co/files/MPEG-4 H.264/4k/Back to the Future (1985) 4k 10bit - 0.10.35-0.11.35.mkv", format="YUV420P10", cache=0, fpsnum=24000, fpsden=1001, prefer_hw=1)
    # Setting color matrix to 2020ncl.
    clip = core.std.SetFrameProps(clip, _Matrix=9)
    clip = clip if not core.text.FrameProps(clip,'_Transfer') else core.std.SetFrameProps(clip, _Transfer=9)
    clip = clip if not core.text.FrameProps(clip,'_Primaries') else core.std.SetFrameProps(clip, _Primaries=9)
    # Setting color range to TV (limited) range.
    clip = core.std.SetFrameProp(clip=clip, prop="_ColorRange", intval=1)
    # making sure frame rate is set to 23.976
    clip = core.std.AssumeFPS(clip=clip, fpsnum=24000, fpsden=1001)
    clip = core.misc.SCDetect(clip=clip,threshold=0.150)
    from vsrife import RIFE
    # adjusting color space from YUV420P10 to RGBS for VsTorchRIFE
    clip = core.resize.Bicubic(clip=clip, format=vs.RGBS, matrix_in_s="2020ncl", range_s="limited")
    # adjusting frame count&rate with RIFE (torch)
    clip = RIFE(clip, scale=0.5, multi=3, device_type='cuda', device_index=0, fp16=True) # new fps: 71.928
    # adjusting output color from: RGBS to YUV420P8 for x264Model
    clip = core.resize.Bicubic(clip=clip, format=vs.YUV420P8, matrix_s="2020ncl", range_s="limited", dither_type="error_diffusion")
    # set output frame rate to 71.928fps
    clip = core.std.AssumeFPS(clip=clip, fpsnum=8991, fpsden=125)
    # Output
    clip.set_output()
    

    tried different scale values, fp16 disabled, without scene change detection and other values for mult, nothing helped. https://github.com/HomeOfVapourSynthEvolution/VapourSynth-RIFE-ncnn-Vulkan works fine. 2k content also works fine. I tried different source filters and different files. Would be nice if this could be fixed.

    attachment was too large: https://ibb.co/WGT9pvL

    opened by Selur 2
  • Vapoursynth R58 and Python 3.10 compatibilty

    Vapoursynth R58 and Python 3.10 compatibilty

    trying to install vs-rife in Vapoursynth R58 I get:

    I:\Hybrid\64bit\Vapoursynth>python -m pip install --upgrade vsrife
    Collecting vsrife
      Using cached vsrife-2.0.0-py3-none-any.whl (32.5 MB)
    Requirement already satisfied: torch>=1.9.0 in i:\hybrid\64bit\vapoursynth\lib\site-packages (from vsrife) (1.11.0+cu113)
    Requirement already satisfied: numpy in i:\hybrid\64bit\vapoursynth\lib\site-packages (from vsrife) (1.22.3)
    Collecting VapourSynth>=55
      Using cached VapourSynth-57.zip (567 kB)
      Preparing metadata (setup.py) ... error
      error: subprocess-exited-with-error
    
      × python setup.py egg_info did not run successfully.
      │ exit code: 1
      ╰─> [15 lines of output]
          Traceback (most recent call last):
            File "C:\Users\Selur\AppData\Local\Temp\pip-install-s7976394\vapoursynth_701a37362cd045f58da4818d07217c99\setup.py", line 64, in <module>
              dll_path = query(winreg.HKEY_LOCAL_MACHINE, REGISTRY_PATH, REGISTRY_KEY)
            File "C:\Users\Selur\AppData\Local\Temp\pip-install-s7976394\vapoursynth_701a37362cd045f58da4818d07217c99\setup.py", line 38, in query
              reg_key = winreg.OpenKey(hkey, path, 0, winreg.KEY_READ)
          FileNotFoundError: [WinError 2] Das System kann die angegebene Datei nicht finden
    
          During handling of the above exception, another exception occurred:
    
          Traceback (most recent call last):
            File "<string>", line 2, in <module>
            File "<pip-setuptools-caller>", line 34, in <module>
            File "C:\Users\Selur\AppData\Local\Temp\pip-install-s7976394\vapoursynth_701a37362cd045f58da4818d07217c99\setup.py", line 67, in <module>
              raise OSError("Couldn't detect vapoursynth installation path")
          OSError: Couldn't detect vapoursynth installation path
          [end of output]
    
      note: This error originates from a subprocess, and is likely not a problem with pip.
    error: metadata-generation-failed
    
    × Encountered error while generating package metadata.
    ╰─> See above for output.
    
    note: This is an issue with the package mentioned above, not pip.
    hint: See above for details.
    

    any idea how to fix it?

    opened by Selur 2
  • How to set 'clip.num_frames

    How to set 'clip.num_frames

    How to set the frames numbers?I only found the "multi: int ="in "init.py".Can I set the whole number of the frames numbers?Like 60 fps?Thanks!

    opened by feaonal 2
  • Requesting example vapoursynth script

    Requesting example vapoursynth script

    I tried to create a valid script for a while, but I can't make it run.

    from vsrife import RIFE
    import vapoursynth as vs
    core = vs.core
    core.std.LoadPlugin(path='/usr/lib/x86_64-linux-gnu/libffms2.so')
    clip = core.ffms2.Source(source='test.webm')
    print(clip) # YUV420P8
    clip = vs.core.resize.Bicubic(clip, format=vs.RGBS)
    print(clip) # RGBS
    clip = RIFE(clip)
    clip.set_output()
    
    vspipe --y4m inference.py - | x264 - --demuxer y4m -o example.mkv
    
    Error: Failed to retrieve frame 0 with error: Resize error: Resize error 3074: no path between colorspaces (2/2/2 => 0/2/2). May need to specify additional colorspace parameters.
    

    Can I get an example that should actually work?

    opened by styler00dollar 2
  • [Q] 0bit models in the repo

    [Q] 0bit models in the repo

    Hi

    i see in the model folders, have a files (models?) with 0bits, i presume when the plugin "learn", the models is filled with the data

    this is correct?

    then, in a system with install this plugin as system-wide, these models should be have a write permissions? (in case of linux)

    greetings

    opened by sl1pkn07 2
  • Wrong output framerate

    Wrong output framerate

    That - https://github.com/HolyWu/vs-rife/blob/91e894f41cbdfb458ef8f776c47c7f652158bc6f/vsrife/init.py#L280 - doesn't work as expected because of two reasons:

    1. clip.fps.numerator / denominator can be 0 / 1 (from the docs: "It is 0/1 when the clip has a variable framerate")
    2. there's a frame duration attached to each frame, and it seems like FrameEval(frame_adjuster) return frames with the original durations, not the ones from format_clip

    A quick fix that works:

        clip0 = vs.core.std.Interleave([clip] * factor_num)
        if factor_den>1:
            clip0 = clip0.std.SelectEvery(cycle=factor_den,offsets=0)
        clip1 = clip.std.DuplicateFrames(frames=clip.num_frames - 1).std.DeleteFrames(frames=0)
        clip1 = vs.core.std.Interleave([clip1] * factor_num)
        if factor_den>1:
            clip1 = clip1.std.SelectEvery(cycle=factor_den,offsets=0)
    
    opened by chainikdn 1
  • How to set clip.num_frames

    How to set clip.num_frames

    How to set the frames numbers?I only found the "multi: int ="in "init.py".Can I set the whole number of the frames numbers?Like 60 fps?Thanks!

    opened by feaonal 0
Releases(v3.1.0)
Owner
null
RIFE - Real-Time Intermediate Flow Estimation for Video Frame Interpolation

RIFE - Real-Time Intermediate Flow Estimation for Video Frame Interpolation YouTube | BiliBili 16X interpolation results from two input images: Introd

旷视天元 MegEngine 28 Dec 9, 2022
FLAVR is a fast, flow-free frame interpolation method capable of single shot multi-frame prediction

FLAVR is a fast, flow-free frame interpolation method capable of single shot multi-frame prediction. It uses a customized encoder decoder architecture with spatio-temporal convolutions and channel gating to capture and interpolate complex motion trajectories between frames to generate realistic high frame rate videos. This repository contains original source code for the paper accepted to CVPR 2021.

Tarun K 280 Dec 23, 2022
This project is based on RIFE and aims to make RIFE more practical for users by adding various features and design new models

This project is based on RIFE and aims to make RIFE more practical for users by adding various features and design new models. Because improving the PSNR index is not compatible with subjective effects, we hope this part of work and our academic research are independent of each other.

hzwer 190 Jan 8, 2023
Asymmetric Bilateral Motion Estimation for Video Frame Interpolation, ICCV2021

ABME (ICCV2021) Junheum Park, Chul Lee, and Chang-Su Kim Official PyTorch Code for "Asymmetric Bilateral Motion Estimation for Video Frame Interpolati

Junheum Park 86 Dec 28, 2022
This is the official repository of XVFI (eXtreme Video Frame Interpolation)

XVFI This is the official repository of XVFI (eXtreme Video Frame Interpolation), https://arxiv.org/abs/2103.16206 Last Update: 20210607 We provide th

Jihyong Oh 195 Dec 29, 2022
Repository relating to the CVPR21 paper TimeLens: Event-based Video Frame Interpolation

TimeLens: Event-based Video Frame Interpolation This repository is about the High Speed Event and RGB (HS-ERGB) dataset, used in the 2021 CVPR paper T

Robotics and Perception Group 544 Dec 19, 2022
an implementation of Revisiting Adaptive Convolutions for Video Frame Interpolation using PyTorch

revisiting-sepconv This is a reference implementation of Revisiting Adaptive Convolutions for Video Frame Interpolation [1] using PyTorch. Given two f

Simon Niklaus 59 Dec 22, 2022
An implementation of Video Frame Interpolation via Adaptive Separable Convolution using PyTorch

This work has now been superseded by: https://github.com/sniklaus/revisiting-sepconv sepconv-slomo This is a reference implementation of Video Frame I

Simon Niklaus 984 Dec 16, 2022
Video Frame Interpolation with Transformer (CVPR2022)

VFIformer Official PyTorch implementation of our CVPR2022 paper Video Frame Interpolation with Transformer Dependencies python >= 3.8 pytorch >= 1.8.0

DV Lab 63 Dec 16, 2022
SE3 Pose Interp - Interpolate camera pose or trajectory in SE3, pose interpolation, trajectory interpolation

SE3 Pose Interpolation Pose estimated from SLAM system are always discrete, and

Ran Cheng 4 Dec 15, 2022
Code of paper "CDFI: Compression-Driven Network Design for Frame Interpolation", CVPR 2021

CDFI (Compression-Driven-Frame-Interpolation) [Paper] (Coming soon...) | [arXiv] Tianyu Ding*, Luming Liang*, Zhihui Zhu, Ilya Zharkov IEEE Conference

Tianyu Ding 95 Dec 4, 2022
Just Go with the Flow: Self-Supervised Scene Flow Estimation

Just Go with the Flow: Self-Supervised Scene Flow Estimation Code release for the paper Just Go with the Flow: Self-Supervised Scene Flow Estimation,

Himangi Mittal 50 Nov 22, 2022
Official project website for the CVPR 2021 paper "Exploring intermediate representation for monocular vehicle pose estimation"

EgoNet Official project website for the CVPR 2021 paper "Exploring intermediate representation for monocular vehicle pose estimation". This repo inclu

Shichao Li 138 Dec 9, 2022
Light-weight network, depth estimation, knowledge distillation, real-time depth estimation, auxiliary data.

light-weight-depth-estimation Boosting Light-Weight Depth Estimation Via Knowledge Distillation, https://arxiv.org/abs/2105.06143 Junjie Hu, Chenyou F

Junjie Hu 13 Dec 10, 2022
A Moonraker plug-in for real-time compensation of frame thermal expansion

Frame Expansion Compensation A Moonraker plug-in for real-time compensation of frame thermal expansion. Installation Credit to protoloft, from whom I

null 58 Jan 2, 2023
Self-Supervised Multi-Frame Monocular Scene Flow (CVPR 2021)

Self-Supervised Multi-Frame Monocular Scene Flow 3D visualization of estimated depth and scene flow (overlayed with input image) from temporally conse

Visual Inference Lab @TU Darmstadt 85 Dec 22, 2022
Unsupervised Learning of Multi-Frame Optical Flow with Occlusions

This is a Pytorch implementation of Janai, J., Güney, F., Ranjan, A., Black, M. and Geiger, A., Unsupervised Learning of Multi-Frame Optical Flow with

Anurag Ranjan 110 Nov 2, 2022
The implemention of Video Depth Estimation by Fusing Flow-to-Depth Proposals

Flow-to-depth (FDNet) video-depth-estimation This is the implementation of paper Video Depth Estimation by Fusing Flow-to-Depth Proposals Jiaxin Xie,

null 32 Jun 14, 2022
EFENet: Reference-based Video Super-Resolution with Enhanced Flow Estimation

EFENet EFENet: Reference-based Video Super-Resolution with Enhanced Flow Estimation Code is a bit messy now. I woud clean up soon. For training the EF

Yaping Zhao 6 Oct 20, 2021