40 citations · 157 across the 30 of their papers we have counts for
9 papers · 1 filter
Mask Grounding for Referring Image Segmentation
Yong Xien Chng, Henry Zheng, Yizeng Han +2
Referring Image Segmentation (RIS) is a challenging task that requires an algorithm to segment objects referred by free-form language expressions. Despite significant progress in r…
GSVA: Generalized Segmentation via Multimodal Large Language Models
Zhuofan Xia, Dongchen Han, Yizeng Han +3
Generalized Referring Expression Segmentation (GRES) extends the scope of classic RES to refer to multiple objects in one expression or identify the empty targets absent in the ima…
Agent Attention: On the Integration of Softmax and Linear Attention
Dongchen Han, Tianzhu Ye, Yizeng Han +5
The attention module is the key component in Transformers. While the global attention mechanism offers high expressiveness, its excessive computational cost restricts its applicabi…
Fine-grained Recognition with Learnable Semantic Data Augmentation
Yifan Pu, Yizeng Han, Yulin Wang +3
Fine-grained image recognition is a longstanding computer vision challenge that focuses on differentiating objects belonging to multiple subordinate categories within the same meta…
FLatten Transformer: Vision Transformer using Focused Linear Attention
Dongchen Han, Xuran Pan, Yizeng Han +2
The quadratic computation complexity of self-attention has been a persistent challenge when applying Transformer models to vision tasks. Linear attention, on the other hand, offers…
Computation-efficient Deep Learning for Computer Vision: A Survey
Yulin Wang, Yizeng Han, Chaofei Wang +3
Over the past decade, deep learning models have exhibited considerable advancements, reaching or even exceeding human-level performance in a range of visual perception tasks. This…
Latency-aware Unified Dynamic Networks for Efficient Image Recognition
Yizeng Han, Zeyu Liu, Zhihang Yuan +4
Dynamic computation has emerged as a promising avenue to enhance the inference efficiency of deep networks. It allows selective activation of computational units, leading to a redu…
Dynamic Perceiver for Efficient Visual Recognition
Yizeng Han, Dongchen Han, Zeyu Liu +7
Early exiting has become a promising approach to improving the inference efficiency of deep networks. By structuring models with multiple classifiers (exits), predictions for ``eas…
Adaptive Rotated Convolution for Rotated Object Detection
Yifan Pu, Yiru Wang, Zhuofan Xia +6
Rotated object detection aims to identify and locate objects in images with arbitrary orientation. In this scenario, the oriented directions of objects vary considerably across dif…