27 citations · 56 across the 7 of their papers we have counts for
7 papers · 1 filter
FADE: A Task-Agnostic Upsampling Operator for Encoder-Decoder Architectures
Hao Lu, Wenze Liu, Hongtao Fu +1
The goal of this work is to develop a task-agnostic feature upsampling operator for dense prediction where the operator is required to facilitate not only region-sensitive tasks li…
SCAPE: A Simple and Strong Category-Agnostic Pose Estimator
Yujia Liang, Zixuan Ye, Wenze Liu +1
Category-Agnostic Pose Estimation (CAPE) aims to localize keypoints on an object of any category given few exemplars in an in-context manner. Prior arts involve sophisticated desig…
Learning to Upsample by Learning to Sample
Wenze Liu, Hao Lu, Hongtao Fu +1
We present DySample, an ultra-lightweight and effective dynamic upsampler. While impressive performance gains have been witnessed from recent kernel-based dynamic upsamplers such a…
Box-DETR: Understanding and Boxing Conditional Spatial Queries
Wenze Liu, Hao Lu, Yuliang Liu +1
Conditional spatial queries are recently introduced into DEtection TRansformer (DETR) to accelerate convergence. In DAB-DETR, such queries are modulated by the so-called conditiona…
On Point Affiliation in Feature Upsampling
Wenze Liu, Hao Lu, Yuliang Liu +1
We introduce the notion of point affiliation into feature upsampling. By abstracting a feature map into non-overlapped semantic clusters formed by points of identical semantic mean…
SAPA: Similarity-Aware Point Affiliation for Feature Upsampling
Hao Lu, Wenze Liu, Zixuan Ye +3
We introduce point affiliation into feature upsampling, a notion that describes the affiliation of each upsampled point to a semantic cluster formed by local decoder feature points…