activity
20102024
most citedDite-HRNet: Dynamic Lightweight High-Resolution Network for Human Pose Estimation

73 citations · 101 across the 13 of their papers we have counts for

collaborators

14 papers

cs.CV2024

Symmetrical Joint Learning Support-query Prototypes for Few-shot Segmentation

Qun Li, Baoquan Sun, Fu Xiao +2

We propose Sym-Net, a novel framework for Few-Shot Segmentation (FSS) that addresses the critical issue of intra-class variation by jointly learning both query and support prototyp…

cs.CV2023

RepSGG: Novel Representations of Entities and Relationships for Scene Graph Generation

Hengyue Liu, Bir Bhanu

Scene Graph Generation (SGG) has achieved significant progress recently. However, most previous works rely heavily on fixed-size entity representations based on bounding box propos…

cs.CV2023★ 1 cited

RECLIP: Resource-efficient CLIP by Training with Small Images

Runze Li, Dahun Kim, Bir Bhanu +1

We present RECLIP (Resource-efficient CLIP), a simple method that minimizes computational resource footprint for CLIP (Contrastive Language Image Pretraining). Inspired by the noti…

cs.CV2022★ 1 cited

MonoIndoor++:Towards Better Practice of Self-Supervised Monocular Depth Estimation for Indoor Environments

Runze Li, Pan Ji, Yi Xu +1

Self-supervised monocular depth estimation has seen significant progress in recent years, especially in outdoor environments. However, depth prediction results are not satisfying i…

cs.CV2022★ 73 cited

Dite-HRNet: Dynamic Lightweight High-Resolution Network for Human Pose Estimation

Qun Li, Ziyi Zhang, Fu Xiao +2

A high-resolution network exhibits remarkable capability in extracting multi-scale features for human pose estimation, but fails to capture long-range interactions between joints a…

cs.CV2021

Transferring Knowledge with Attention Distillation for Multi-Domain Image-to-Image Translation

Runze Li, Tomaso Fontanini, Luca Donati +2

Gradient-based attention modeling has been used widely as a way to visualize and understand convolutional neural networks. However, exploiting these visual explanations during the…