深度估计近年来顶会顶刊汇总_全景图像深度估计 相关顶会

CVPR 2023

ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth
Monocular Depth Estimation using Diffusion Models

CVPR 2021

[10] Self-supervised Learning of Depth Inference for Multi-view Stereo(多视图立体声深度推理的自我监督学习)
paper | code
[9] Depth Completion with Twin Surface Extrapolation at Occlusion Boundaries(遮挡边界处的深度补全和双曲面外推)
paper
[8] S2R-DepthNet: Learning a Generalizable Depth-specific Structural Representation(学习通用的深度特定的结构表示)
paper
[7] RGB-D Local Implicit Function for Depth Completion of Transparent Objects(RGB-D局部隐式函数用于透明对象的深度补全)
paper | code
[6] LED2-Net: Monocular 360 Layout Estimation via Differentiable Depth Rendering(通过可分辨深度渲染进行单眼360布局估算)
paper | project
[5] Deep Two-View Structure-from-Motion Revisited(重新审视运动的深层两视图结构)
paper
[4] Mask-ToF: Learning Microlens Masks for Flying Pixel Correction in Time-of-Flight Imaging(学习微透镜掩模以在飞行时间成像中进行飞行像素校正)
paper | project
[3] Generalizing to the Open World: Deep Visual Odometry with Online Adaptation(推广到开放世界：具有在线适应功能的深度视觉里程表)
paper
[2] Beyond Image to Depth: Improving Depth Prediction using Echoes(超越图像深度：使用回声改善深度预测)
paper | code
[1] PLADE-Net: Towards Pixel-Level Accuracy for Self-Supervised Single-View Depth Estimation with Neural Positional Encoding and Distilled Matting Loss(具有神经位置编码和蒸馏消光损耗的自我监督单视图深度估计的像素级精度)paper

CVPR2022

[12] Practical Stereo Matching via Cascaded Recurrent Network with Adaptive Correlation(基于自适应相关的级联循环网络的实用立体匹配)paper | project
[11] Depth Estimation by Combining Binocular Stereo and Monocular Structured-Light(结合双目立体和单目结构光的深度估计)paper | code
[10] RGB-Depth Fusion GAN for Indoor Depth Completion(用于室内深度完成的 RGB 深度融合 GAN)paper
[9] Revisiting Domain Generalized Stereo Matching Networks from a Feature Consistency Perspective(从特征一致性的角度重新审视域广义立体匹配网络)paper
[8] Deep Depth from Focus with Differential Focus Volume(具有不同焦点体积的焦点深度)paper
[7] ChiTransformer:Towards Reliable Stereo from Cues(从线索走向可靠的立体声)paper
[6] Rethinking Depth Estimation for Multi-View Stereo: A Unified Representation and Focal Loss(重新思考多视图立体的深度估计：统一表示和焦点损失)paper | code
[5] ITSA: An Information-Theoretic Approach to Automatic Shortcut Avoidance and Domain Generalization in Stereo Matching Networks(立体匹配网络中自动避免捷径和域泛化的信息论方法)paper
[4] Attention Concatenation Volume for Accurate and Efficient Stereo Matching(用于精确和高效立体匹配的注意力连接体积) paper | code
[3] Occlusion-Aware Cost Constructor for Light Field Depth Estimation(光场深度估计的遮挡感知成本构造函数)paper | [code](https://github.com/YingqianWang/OACC- Net)
[2] NeW CRFs: Neural Window Fully-connected CRFs for Monocular Depth Estimation(用于单目深度估计的神经窗口全连接 CRF) paper
[1] OmniFusion: 360 Monocular Depth Estimation via Geometry-Aware Fusion(通过几何感知融合进行 360 度单目深度估计)paper

ICCV2021

深度估计(Depth Estimation)
[7] PatchMatch-RL: Deep MVS with Pixelwise Depth, Normal, and Visibility(Oral) PatchMatch-RL:深度MVS像素化深度，正常，可见度(口头)
paper | code
[6] Fine-grained Semantics-aware Representation Enhancement for Self-supervised Monocular Depth Estimation(Oral) 自监督单眼深度估计的细粒度语义感知表示增强(口头)
paper | code
[5] StructDepth: Leveraging the structural regularities for self-supervised indoor depth estimation StructDepth:利用结构规律进行自我监督的室内深度估计
paper | code
[4] Self-supervised Monocular Depth Estimation for All Day Images using Domain Separation使用域分离的全天图像的自监督单目深度估计
paper
[3] Towards Interpretable Deep Networks for Monocular Depth Estimation用于单目深度估计的可解释深度网络研究
paper | code
[2] Regularizing Nighttime Weirdness: Efficient Self-supervised Monocular Depth Estimation in the Dark规范夜间怪异:在黑暗中有效的自我监督单目深度估计
paper
[1] MonoIndoor: Towards Good Practice of Self-Supervised Monocular Depth Estimation for Indoor Environments单室内:迈向室内环境自我监督单目深度估计的良好实践
paper

ECCV2020

P2Net: Patch-match and Plane-regularization for Unsupervised Indoor Depth Estimation
P2Net:无监督室内深度估计的Patch-match和平面正则化
• 论文：https://arxiv.org/abs/2007.07696
• 代码：https://github.com/svip-lab/Indoor-SfMLearner
Self-Supervised Monocular Depth Estimation: Solving the Dynamic Object Problem by Semantic Guidance
自监督单目深度估计:通过语义引导解决动态对象问题
• 论文：https://arxiv.org/abs/2007.06936
• 代码：https://github.com/ifnspaml/SGDepth
Non-Local Spatial Propagation Network for Depth Completion
用于深度补井的非局部空间传播网络
• 论文：https://arxiv.org/abs/2007.10042
• 代码：https://github.com/zzangjinsun/NLSPN_ECCV20

ECCV2022

[1] Physical Attack on Monocular Depth Estimation with Optimal Adversarial Patches ((使用最优对抗补丁对单目深度估计进行物理攻击))
paper