16 citations · 75 across the 14 of their papers we have counts for
15 papers
FlowFormer: A Transformer Architecture and Its Masked Cost Volume Autoencoding for Optical Flow
Zhaoyang Huang, Xiaoyu Shi, Chao Zhang +6
This paper introduces a novel transformer-based network architecture, FlowFormer, along with the Masked Cost Volume AutoEncoding (MCVA) for pretraining it to tackle the problem of…
Context-PIPs: Persistent Independent Particles Demands Spatial Context Features
Weikang Bian, Zhaoyang Huang, Xiaoyu Shi +3
We tackle the problem of Persistent Independent Particles (PIPs), also called Tracking Any Point (TAP), in videos, which specifically aims at estimating persistent long-term trajec…
DiffInDScene: Diffusion-based High-Quality 3D Indoor Scene Generation
Xiaoliang Ju, Zhaoyang Huang, Yijin Li +3
We present DiffInDScene, a novel framework for tackling the problem of high-quality 3D indoor scene generation, which is challenging due to the complexity and diversity of the indo…
FlowFormer++: Masked Cost Volume Autoencoding for Pretraining Optical Flow Estimation
Xiaoyu Shi, Zhaoyang Huang, Dasong Li +6
FlowFormer introduces a transformer architecture into optical flow estimation and achieves state-of-the-art performance. The core component of FlowFormer is the transformer-based c…
VideoFlow: Exploiting Temporal Cues for Multi-frame Optical Flow Estimation
Xiaoyu Shi, Zhaoyang Huang, Weikang Bian +7
We introduce VideoFlow, a novel optical flow estimation framework for videos. In contrast to previous methods that learn to estimate optical flow from two frames, VideoFlow concurr…
BlinkFlow: A Dataset to Push the Limits of Event-based Optical Flow Estimation
Yijin Li, Zhaoyang Huang, Shuo Chen +5
Event cameras provide high temporal precision, low data rates, and high dynamic range visual perception, which are well-suited for optical flow estimation. While data-driven optica…