3 citations · 9 across the 19 of their papers we have counts for
19 papers
When Rewards Disagree: Reward Weighting for Token-Efficient Video Reasoning
Zinuo Li, Yongxin Guo, Jun Liu +7
Human perception interprets video dynamics by constructing structured mental representations of entities, actions, and temporal boundaries before engaging in high-level reasoning.…
Controllable Complex Human Motion Video Generation via Text-to-Skeleton Cascades
Ashkan Taghipour, Morteza Ghahremani, Zinuo Li +3
Generating videos of complex human motions such as flips, cartwheels, and martial arts remains challenging for current video diffusion models. Text-only conditioning is temporally…
EvoFSM: Controllable Self-Evolution for Deep Research with Finite State Machines
Shuo Zhang, Chaofa Yuan, Ryan Guo +11
While LLM-based agents have shown promise for deep research, most existing approaches rely on fixed workflows that struggle to adapt to real-world, open-ended queries. Recent work…
AdaRD-key: Adaptive Relevance-Diversity Keyframe Sampling for Long-form Video understanding
Xian Zhang, Zexi Wu, Zinuo Li +5
Understanding long-form videos remains a significant challenge for vision--language models (VLMs) due to their extensive temporal length and high information density. Most current…
LatentMove: Towards Complex Human Movement Video Generation
Ashkan Taghipour, Morteza Ghahremani, Mohammed Bennamoun +5
Image-to-video (I2V) generation seeks to produce realistic motion sequences from a single reference image. Although recent methods exhibit strong temporal consistency, they often s…
Watch and Listen: Understanding Audio-Visual-Speech Moments with Multimodal LLM
Zinuo Li, Xian Zhang, Yongxin Guo +5
Humans naturally understand moments in a video by integrating visual and auditory cues. For example, localizing a scene in the video like "A scientist passionately speaks on wildli…
Unifying Interpretations of Phase Transitions in the Vicsek Model: Correlation Length as a Diagnostic Tool
Wenhao Yu, Zinuo Li, Liufang Xu
Vicsek Model is widely used in simulations of dry active matter. We re-examined two typical phase transitions in the original Vicsek model by using the velocity correlation length.…
Layer-Wise Feature Metric of Semantic-Pixel Matching for Few-Shot Learning
Hao Tang, Junhao Lu, Guoheng Huang +5
In Few-Shot Learning (FSL), traditional metric-based approaches often rely on global metrics to compute similarity. However, in natural scenes, the spatial arrangement of key insta…
Faster Image2Video Generation: A Closer Look at CLIP Image Embedding's Impact on Spatio-Temporal Cross-Attentions
Ashkan Taghipour, Morteza Ghahremani, Mohammed Bennamoun +4
This paper investigates the role of CLIP image embeddings within the Stable Video Diffusion (SVD) framework, focusing on their impact on video generation quality and computational…
QEAN: Quaternion-Enhanced Attention Network for Visual Dance Generation
Zhizhen Zhou, Yejing Huo, Guoheng Huang +4
The study of music-generated dance is a novel and challenging Image generation task. It aims to input a piece of music and seed motions, then generate natural dance movements for t…
CLIP Guided Image-perceptive Prompt Learning for Image Enhancement
Weiwen Chen, Qiuhong Ke, Zinuo Li
Image enhancement is a significant research area in the fields of computer vision and image processing. In recent years, many learning-based methods for image enhancement have been…
UWFormer: Underwater Image Enhancement via a Semi-Supervised Multi-Scale Transformer
Weiwen Chen, Yingtie Lei, Shenghong Luo +3
Underwater images often exhibit poor quality, distorted color balance and low contrast due to the complex and intricate interplay of light, water, and objects. Despite the signific…
ShaDocFormer: A Shadow-Attentive Threshold Detector With Cascaded Fusion Refiner for Document Shadow Removal
Weiwen Chen, Yingtie Lei, Shenghong Luo +3
Document shadow is a common issue that arises when capturing documents using mobile devices, which significantly impacts readability. Current methods encounter various challenges,…
High-Resolution Document Shadow Removal via A Large-Scale Real-World Dataset and A Frequency-Aware Shadow Erasing Net
Zinuo Li, Xuhang Chen, Chi-Man Pun +1
Shadows often occur when we capture the documents with casual equipment, which influences the visual quality and readability of the digital copies. Different from the algorithms fo…
Devignet: High-Resolution Vignetting Removal via a Dual Aggregated Fusion Transformer With Adaptive Channel Expansion
Shenghong Luo, Xuhang Chen, Weiwen Chen +3
Vignetting commonly occurs as a degradation in images resulting from factors such as lens design, improper lens hood usage, and limitations in camera sensors. This degradation affe…
DocDeshadower: Frequency-Aware Transformer for Document Shadow Removal
Ziyang Zhou, Yingtie Lei, Xuhang Chen +4
Shadows in scanned documents pose significant challenges for document analysis and recognition tasks due to their negative impact on visual quality and readability. Current shadow…
A Large-scale Film Style Dataset for Learning Multi-frequency Driven Film Enhancement
Zinuo Li, Xuhang Chen, Shuqiang Wang +1
Film, a classic image style, is culturally significant to the whole photographic industry since it marks the birth of photography. However, film photography is time-consuming and e…
WavEnhancer: Unifying Wavelet and Transformer for Image Enhancement
Zinuo Li, Xuhang Chen, Chi-Man Pun +1
Image enhancement is a technique that frequently utilized in digital image processing. In recent years, the popularity of learning-based techniques for enhancing the aesthetic perf…
Fast fluorescence lifetime imaging analysis via extreme learning machine
Zhenya Zang, Dong Xiao, Quan Wang +4
We present a fast and accurate analytical method for fluorescence lifetime imaging microscopy (FLIM) using the extreme learning machine (ELM). We used extensive metrics to evaluate…