1 citations · 2 across the 6 of their papers we have counts for
7 papers
Octopus: Alleviating Hallucination via Dynamic Contrastive Decoding
Wei Suo, Lijun Zhang, Mengyang Sun +3
Large Vision-Language Models (LVLMs) have obtained impressive performance in visual content understanding and multi-modal reasoning. Unfortunately, these large models suffer from s…
Pruning All-Rounder: Rethinking and Improving Inference Efficiency for Large Vision Language Models
Wei Suo, Ji Ma, Mengyang Sun +3
Although Large Vision-Language Models (LVLMs) have achieved impressive results, their high computational costs pose a significant barrier to wide application. To enhance inference…
Visual Prompt Selection for In-Context Learning Segmentation
Wei Suo, Lanqing Lai, Mengyang Sun +3
As a fundamental and extensively studied task in computer vision, image segmentation aims to locate and identify different semantic concepts at the pixel level. Recently, inspired…
S3C: Semi-Supervised VQA Natural Language Explanation via Self-Critical Learning
Wei Suo, Mengyang Sun, Weisong Liu +4
VQA Natural Language Explanation (VQA-NLE) task aims to explain the decision-making process of VQA models in natural language. Unlike traditional attention or gradient analysis, fr…
Dual-Level Decoupled Transformer for Video Captioning
Yiqi Gao, Xinglin Hou, Wei Suo +4
Video captioning aims to understand the spatio-temporal semantic concept of the video and generate descriptive sentences. The de-facto approach to this task dictates a text generat…
Proposal-free One-stage Referring Expression via Grid-Word Cross-Attention
Wei Suo, Mengyang Sun, Peng Wang +1
Referring Expression Comprehension (REC) has become one of the most important tasks in visual reasoning, since it is an essential step for many vision-and-language tasks such as vi…
Combining Pyramid Pooling and Attention Mechanism for Pelvic MR Image Semantic Segmentaion
Ting-Ting Liang, Satoshi Tsutsui, Liangcai Gao +2
One of the time-consuming routine work for a radiologist is to discern anatomical structures from tomographic images. For assisting radiologists, this paper develops an automatic s…