ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2110.06635
  4. Cited By
ADOP: Approximate Differentiable One-Pixel Point Rendering

ADOP: Approximate Differentiable One-Pixel Point Rendering

13 October 2021
Darius Ruckert
Linus Franke
Marc Stamminger
    3DPC
ArXivPDFHTML

Papers citing "ADOP: Approximate Differentiable One-Pixel Point Rendering"

12 / 62 papers shown
Title
Learning Efficient Point Cloud Generation for Dense 3D Object
  Reconstruction
Learning Efficient Point Cloud Generation for Dense 3D Object Reconstruction
Chen-Hsuan Lin
Chen Kong
Simon Lucey
3DV
72
426
0
21 Jun 2017
Multi-view Supervision for Single-view Reconstruction via Differentiable
  Ray Consistency
Multi-view Supervision for Single-view Reconstruction via Differentiable Ray Consistency
Shubham Tulsiani
Tinghui Zhou
Alyosha A. Efros
Jitendra Malik
3DV
81
560
0
20 Apr 2017
ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D
  Cameras
ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D Cameras
Raul Mur-Artal
Juan D. Tardós
345
5,440
0
20 Oct 2016
DeepWarp: Photorealistic Image Resynthesis for Gaze Manipulation
DeepWarp: Photorealistic Image Resynthesis for Gaze Manipulation
Yaroslav Ganin
Daniil Kononenko
Diana Sungatullina
Victor Lempitsky
CVBM
55
122
0
25 Jul 2016
Direct Sparse Odometry
Direct Sparse Odometry
Jakob Engel
V. Koltun
Daniel Cremers
86
2,526
0
09 Jul 2016
View Synthesis by Appearance Flow
View Synthesis by Appearance Flow
Tinghui Zhou
Shubham Tulsiani
Weilun Sun
Jitendra Malik
Alexei A. Efros
126
692
0
11 May 2016
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
Justin Johnson
Alexandre Alahi
Li Fei-Fei
SupR
234
10,249
0
27 Mar 2016
A Versatile Scene Model with Differentiable Visibility Applied to
  Generative Pose Estimation
A Versatile Scene Model with Differentiable Visibility Applied to Generative Pose Estimation
Helge Rhodin
Nadia Robertini
Christian Richardt
Hans-Peter Seidel
Christian Theobalt
3DV
3DH
68
97
0
11 Feb 2016
DeepStereo: Learning to Predict New Views from the World's Imagery
DeepStereo: Learning to Predict New Views from the World's Imagery
John Flynn
Ivan Neulander
James Philbin
Noah Snavely
3DV
117
652
0
22 Jun 2015
Empirical Evaluation of Rectified Activations in Convolutional Network
Empirical Evaluation of Rectified Activations in Convolutional Network
Bing Xu
Naiyan Wang
Tianqi Chen
Mu Li
135
2,912
0
05 May 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.8K
150,115
0
22 Dec 2014
Caffe: Convolutional Architecture for Fast Feature Embedding
Caffe: Convolutional Architecture for Fast Feature Embedding
Yangqing Jia
Evan Shelhamer
Jeff Donahue
Sergey Karayev
Jonathan Long
Ross B. Girshick
S. Guadarrama
Trevor Darrell
VLM
BDL
3DV
274
14,710
0
20 Jun 2014
Previous
12