30 citations · 184 across the 30 of their papers we have counts for
29 papers · 1 filter
Parametric Depth Based Feature Representation Learning for Object Detection and Segmentation in Bird's Eye View
Jiayu Yang, Enze Xie, Miaomiao Liu +1
Recent vision-only perception models for autonomous driving achieved promising results by encoding multi-view image features into Bird's-Eye-View (BEV) space. A critical step and t…
LDP: Language-driven Dual-Pixel Image Defocus Deblurring Network
Hao Yang, Liyuan Pan, Yan Yang +2
Recovering sharp images from dual-pixel (DP) pairs with disparity-dependent blur is a challenging task.~Existing blur map-based deblurring methods have demonstrated promising resul…
VisFusion: Visibility-aware Online 3D Scene Reconstruction from Videos
Huiyu Gao, Wei Mao, Miaomiao Liu
We propose VisFusion, a visibility-aware online 3D scene reconstruction approach from posed monocular videos. In particular, we aim to reconstruct the scene from volumetric feature…
Contact-aware Human Motion Forecasting
Wei Mao, Miaomiao Liu, Richard Hartley +1
In this paper, we tackle the task of scene-aware 3D human motion forecasting, which consists of predicting future human poses given a 3D scene and a past human motion. A key challe…
Weakly-supervised Action Transition Learning for Stochastic Human Motion Prediction
Wei Mao, Miaomiao Liu, Mathieu Salzmann
We introduce the task of action-driven stochastic human motion prediction, which aims to predict multiple plausible future motions given a sequence of action labels and a short mot…
Non-parametric Depth Distribution Modelling based Depth Inference for Multi-view Stereo
Jiayu Yang, Jose M. Alvarez, Miaomiao Liu
Recent cost volume pyramid based deep neural networks have unlocked the potential of efficiently leveraging high-resolution images for depth inference from multi-view stereo. In ge…
SPA-VAE: Similar-Parts-Assignment for Unsupervised 3D Point Cloud Generation
Shidi Li, Christian Walder, Miaomiao Liu
This paper addresses the problem of unsupervised parts-aware point cloud generation with learned parts-based self-similarity. Our SPA-VAE infers a set of latent canonical candidate…
EditVAE: Unsupervised Part-Aware Controllable 3D Point Cloud Shape Generation
Shidi Li, Miaomiao Liu, Christian Walder
This paper tackles the problem of parts-aware point cloud generation. Unlike existing works which require the point cloud to be segmented into parts a priori, our parts-aware editi…
Generating Smooth Pose Sequences for Diverse Human Motion Prediction
Wei Mao, Miaomiao Liu, Mathieu Salzmann
Recent progress in stochastic motion prediction, i.e., predicting multiple possible future human motions given a single past pose sequence, has led to producing truly diverse futur…
Multi-level Motion Attention for Human Motion Prediction
Wei Mao, Miaomiao Liu, Mathieu Salzmann +1
Human motion prediction aims to forecast future human poses given a historical motion. Whether based on recurrent or feed-forward neural networks, existing learning based methods f…
Spatially Invariant Unsupervised 3D Object-Centric Learning and Scene Decomposition
Tianyu Wang, Miaomiao Liu, Kee Siong Ng
We tackle the problem of object-centric learning on point clouds, which is crucial for high-level relational reasoning and scalable machine intelligence. In particular, we introduc…
Self-supervised Learning of Depth Inference for Multi-view Stereo
Jiayu Yang, Jose M. Alvarez, Miaomiao Liu
Recent supervised multi-view depth estimation networks have achieved promising results. Similar to all supervised approaches, these networks require ground-truth data during traini…
Fixed Viewpoint Mirror Surface Reconstruction under an Uncalibrated Camera
Kai Han, Miaomiao Liu, Dirk Schnieders +1
This paper addresses the problem of mirror surface reconstruction, and proposes a solution based on observing the reflections of a moving reference plane on the mirror surface. Unl…
Dual Pixel Exploration: Simultaneous Depth Estimation and Image Restoration
Liyuan Pan, Shah Chowdhury, Richard Hartley +3
The dual-pixel (DP) hardware works by splitting each pixel in half and creating an image pair in a single snapshot. Several works estimate depth/inverse depth by treating the DP pa…
History Repeats Itself: Human Motion Prediction via Motion Attention
Wei Mao, Miaomiao Liu, Mathieu Salzmann
Human motion prediction aims to forecast future human poses given a past motion. Whether based on recurrent or feed-forward neural networks, existing methods fail to model the obse…
Single Image Optical Flow Estimation with an Event Camera
Liyuan Pan, Miaomiao Liu, Richard Hartley
Event cameras are bio-inspired sensors that asynchronously report intensity changes in microsecond resolution. DAVIS can capture high dynamics of a scene and simultaneously output…
Joint Unsupervised Learning of Optical Flow and Egomotion with Bi-Level Optimization
Shihao Jiang, Dylan Campbell, Miaomiao Liu +2
We address the problem of joint optical flow and camera motion estimation in rigid scenes by incorporating geometric constraints into an unsupervised deep learning framework. Unlik…
Cost Volume Pyramid Based Depth Inference for Multi-View Stereo
Jiayu Yang, Wei Mao, Jose M. Alvarez +1
We propose a cost volume-based neural network for depth inference from multi-view images. We demonstrate that building a cost volume pyramid in a coarse-to-fine manner instead of c…
Joint Stereo Video Deblurring, Scene Flow Estimation and Moving Object Segmentation
Liyuan Pan, Yuchao Dai, Miaomiao Liu +2
Stereo videos for the dynamic scenes often show unpleasant blurred effects due to the camera motion and the multiple moving objects with large depth variations. Given consecutive b…
Learning Trajectory Dependencies for Human Motion Prediction
Wei Mao, Miaomiao Liu, Mathieu Salzmann +1
Human motion prediction, i.e., forecasting future body poses given observed pose sequence, has typically been tackled with recurrent neural networks (RNNs). However, as evidenced b…
High Frame Rate Video Reconstruction based on an Event Camera
Liyuan Pan, Richard Hartley, Cedric Scheerlinck +3
Event-based cameras measure intensity changes (called `events') with microsecond accuracy under high-speed motion and challenging lighting conditions. With the `active pixel sensor…
Single Image Deblurring and Camera Motion Estimation with Depth Map
Liyuan Pan, Yuchao Dai, Miaomiao Liu
Camera shake during exposure is a major problem in hand-held photography, as it causes image blur that destroys details in the captured images.~In the real world, such blur is main…
Bringing a Blurry Frame Alive at High Frame-Rate with an Event Camera
Liyuan Pan, Cedric Scheerlinck, Xin Yu +3
Event-based cameras can measure intensity changes (called `{\it events}') with microsecond accuracy under high-speed motion and challenging lighting conditions. With the active pix…
Phase-only Image Based Kernel Estimation for Single-image Blind Deblurring
Liyuan Pan, Richard Hartley, Miaomiao Liu +1
The image blurring process is generally modelled as the convolution of a blur kernel with a latent image. Therefore, the estimation of the blur kernel is essentially important for…