32 citations · 49 across the 9 of their papers we have counts for
9 papers
SpaCE-10: A Comprehensive Benchmark for Multimodal Large Language Models in Compositional Spatial Intelligence
Ziyang Gong, Wenhao Li, Oliver Ma +7
Multimodal Large Language Models (MLLMs) have achieved remarkable progress in various multimodal tasks. To pursue higher intelligence in space, MLLMs require integrating multiple s…
Towards General Visual-Linguistic Face Forgery Detection(V2)
Ke Sun, Shen Chen, Taiping Yao +5
Face manipulation techniques have achieved significant advances, presenting serious challenges to security and social trust. Recent works demonstrate that leveraging multimodal mod…
Long-VITA: Scaling Large Multi-modal Models to 1 Million Tokens with Leading Short-Context Accuracy
Yunhang Shen, Chaoyou Fu, Shaoqi Dong +14
We introduce Long-VITA, a simple yet effective large multi-modal model for long-context visual-language understanding tasks. It is adept at concurrently processing and analyzing mo…
TraDiffusion: Trajectory-Based Training-Free Image Generation
Mingrui Wu, Oucheng Huang, Jiayi Ji +6
In this work, we propose a training-free, trajectory-based controllable T2I approach, termed TraDiffusion. This novel method allows users to effortlessly guide image generation via…
Beyond Inter-Item Relations: Dynamic Adaption for Enhancing LLM-Based Sequential Recommendation
CanYi Liu, Wei Li, Youchen +3
Sequential recommender systems (SRS) predict the next items that users may prefer based on user historical interaction sequences. Inspired by the rise of large language models (LLM…
Less is More: Learning Reference Knowledge Using No-Reference Image Quality Assessment
Xudong Li, Jingyuan Zheng, Xiawu Zheng +9
Image Quality Assessment (IQA) with reference images have achieved great success by imitating the human vision system, in which the image quality is effectively assessed by compari…
Towards General Visual-Linguistic Face Forgery Detection
Ke Sun, Shen Chen, Taiping Yao +4
Deepfakes are realistic face manipulations that can pose serious threats to security, privacy, and trust. Existing methods mostly treat this task as binary classification, which us…
PAMS: Quantized Super-Resolution via Parameterized Max Scale
Huixia Li, Chenqian Yan, Shaohui Lin +5
Deep convolutional neural networks (DCNNs) have shown dominant performance in the task of super-resolution (SR). However, their heavy memory cost and computation overhead significa…
Pyramidal Person Re-IDentification via Multi-Loss Dynamic Training
Feng Zheng, Cheng Deng, Xing Sun +5
Most existing Re-IDentification (Re-ID) methods are highly dependent on precise bounding boxes that enable images to be aligned with each other. However, due to the challenging pra…