Search Results for author: Ruoteng Li

Found 14 papers, 2 papers with code

Object Tracking using Spatio-Temporal Networks for Future Prediction Location

no code implementations ECCV 2020 Yuan Liu, Ruoteng Li, Yu Cheng, Robby T. Tan, Xiubao Sui

To facilitate the future prediction ability, we follow three key observations: 1) object motion trajectory is affected significantly by camera motion; 2) the past trajectory of an object can act as a salient cue to estimate the object motion in the spatial domain; 3) previous frames contain the surroundings and appearance of the target object, which is useful for predicting the target object’s future locations.

Future prediction Object +1

AdAM: Few-Shot Image Generation via Adaptation-Aware Kernel Modulation

no code implementations4 Jul 2023 Yunqing Zhao, Keshigeyan Chandrasegaran, Milad Abdollahzadeh, Chao Du, Tianyu Pang, Ruoteng Li, Henghui Ding, Ngai-Man Cheung

However, a major limitation of existing methods is that their knowledge preserving criteria consider only source domain/task and fail to consider target domain/adaptation in selecting source knowledge, casting doubt on their suitability for setups of different proximity between source and target domain.

Domain Adaptation Image Generation

Estimating Reflectance Layer from A Single Image: Integrating Reflectance Guidance and Shadow/Specular Aware Learning

1 code implementation27 Nov 2022 Yeying Jin, Ruoteng Li, Wenhan Yang, Robby T. Tan

To further enforce the reflectance layer to be independent of shadows and specularities in the second-stage refinement, we introduce an S-Aware network that distinguishes the reflectance image from the input image.

highlight removal Intrinsic Image Decomposition +1

Object Tracking Using Spatio-Temporal Future Prediction

no code implementations15 Oct 2020 YuAn Liu, Ruoteng Li, Robby T. Tan, Yu Cheng, Xiubao Sui

Our trajectory prediction module predicts the target object's locations in the current and future frames based on the object's past trajectory.

Future prediction Object +2

All in One Bad Weather Removal Using Architectural Search

no code implementations CVPR 2020 Ruoteng Li, Robby T. Tan, Loong-Fah Cheong

In this paper, we propose a method that can handle multiple bad weather degradations: rain, fog, snow and adherent raindrops using a single network.

Image Restoration Neural Architecture Search +1

Realistic Large-Scale Fine-Depth Dehazing Dataset from 3D Videos

no code implementations18 Apr 2020 Ruoteng Li, Xiaoyi Zhang, ShaoDi You, Yu Li

We select a large number of high-quality frames of real outdoor scenes and render haze on them using depth from stereo.

Autonomous Driving Benchmarking +1

Single image reflection removal via learning with multi-image constraints

no code implementations8 Dec 2019 Yingda Yin, Qingnan Fan, Dong-Dong Chen, Yujie Wang, Angelica Aviles-Rivero, Ruoteng Li, Carola-Bibiane Schnlieb, Baoquan Chen

Reflections are very common phenomena in our daily photography, which distract people's attention from the scene behind the glass.

Reflection Removal

RainFlow: Optical Flow Under Rain Streaks and Rain Veiling Effect

no code implementations ICCV 2019 Ruoteng Li, Robby T. Tan, Loong-Fah Cheong, Angelica I. Aviles-Rivero, Qingnan Fan, Carola-Bibiane Schonlieb

We introduce a feature multiplier in our network that transforms the features of an image affected by the rain veiling effect into features that are less affected by it, which we call veiling-invariant features.

Optical Flow Estimation

Heavy Rain Image Restoration: Integrating Physics Model and Conditional Adversarial Learning

1 code implementation CVPR 2019 Ruoteng Li, Loong-Fah Cheong, Robby T. Tan

This filtering is guided by a rain-free residue image --- its content is used to set the passbands for the two channels in a spatially-variant manner so that the background details do not get mixed up with the rain-streaks.

Image Restoration Rain Removal

Robust Optical Flow in Rainy Scenes

no code implementations ECCV 2018 Ruoteng Li, Robby T. Tan, Loong-Fah Cheong

Optical flow estimation in rainy scenes is challenging due to degradation caused by rain streaks and rain accumulation, where the latter refers to the poor visibility of remote scenes due to intense rainfall.

Optical Flow Estimation

Single Image Deraining using Scale-Aware Multi-Stage Recurrent Network

no code implementations19 Dec 2017 Ruoteng Li, Loong-Fah Cheong, Robby T. Tan

Given a single input rainy image, our goal is to visually remove rain streaks and the veiling effect caused by scattering and transmission of rain streaks and rain droplets.

Single Image Deraining

Robust Optical Flow Estimation in Rainy Scenes

no code implementations18 Apr 2017 Ruoteng Li, Robby T. Tan, Loong-Fah Cheong

To handle rain accumulation, our method decomposes the image into a piecewise-smooth background layer and a high-frequency detail layer.

Optical Flow Estimation

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