Cover Image

SlowFocus: Enhancing Fine-grained Temporal Understanding in Video LLM

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Nie, Ming, Ding, Dan, Wang, Chunwei, Guo, Yuanfan, Han, Jianhua, Xu, Hang, Zhang, Li
Format:	Preprint
Published:	2026
Subjects:	Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

KFFocus: Highlighting Keyframes for Enhanced Video Understanding
by: Nie, Ming, et al.
Published: (2025)

Brick-Diffusion: Generating Long Videos with Brick-to-Wall Denoising
by: Yuan, Yunlong, et al.
Published: (2025)

Towards Unified Multimodal Interleaved Generation via Group Relative Policy Optimization
by: Nie, Ming, et al.
Published: (2026)

Reason2Drive: Towards Interpretable and Chain-based Reasoning for Autonomous Driving
by: Nie, Ming, et al.
Published: (2023)

VTimeCoT: Thinking by Drawing for Video Temporal Grounding and Reasoning
by: Zhang, Jinglei, et al.
Published: (2025)

EasyControl: Transfer ControlNet to Video Diffusion for Controllable Generation and Interpolation
by: Wang, Cong, et al.
Published: (2024)

Focus Anywhere for Fine-grained Multi-page Document Understanding
by: Liu, Chenglong, et al.
Published: (2024)

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos
by: Kong, Fanheng, et al.
Published: (2025)

GLaVE-Cap: Global-Local Aligned Video Captioning with Vision Expert Integration
by: Xu, Wan, et al.
Published: (2025)

ILLUME: Illuminating Your LLMs to See, Draw, and Self-Enhance
by: Wang, Chunwei, et al.
Published: (2024)

PaMi-VDPO: Mitigating Video Hallucinations by Prompt-Aware Multi-Instance Video Preference Learning
by: Ding, Xinpeng, et al.
Published: (2025)

Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
by: Wang, Haibo, et al.
Published: (2024)

WTS: A Pedestrian-Centric Traffic Video Dataset for Fine-grained Spatial-Temporal Understanding
by: Kong, Quan, et al.
Published: (2024)

HumanRefiner: Benchmarking Abnormal Human Generation and Refining with Coarse-to-fine Pose-Reversible Guidance
by: Fang, Guian, et al.
Published: (2024)

HiLM-D: Enhancing MLLMs with Multi-Scale High-Resolution Details for Autonomous Driving
by: Ding, Xinpeng, et al.
Published: (2023)

MA-Bench: Towards Fine-grained Micro-Action Understanding
by: Li, Kun, et al.
Published: (2026)

TemporalBench: Benchmarking Fine-grained Temporal Understanding for Multimodal Video Models
by: Cai, Mu, et al.
Published: (2024)

FiLA-Video: Spatio-Temporal Compression for Fine-Grained Long Video Understanding
by: Guo, Yanan, et al.
Published: (2025)

V-CORE: Temporally Consistent Video Understanding for Video-LLM
by: Kang, Zhengjian, et al.
Published: (2026)

UNIT: Unifying Image and Text Recognition in One Vision Encoder
by: Zhu, Yi, et al.
Published: (2024)

Mesh-RFT: Enhancing Mesh Generation via Fine-grained Reinforcement Fine-Tuning
by: Liu, Jian, et al.
Published: (2025)

SemHiTok: A Unified Image Tokenizer via Semantic-Guided Hierarchical Codebook for Multimodal Understanding and Generation
by: Chen, Zisheng, et al.
Published: (2025)

Large-scale and Fine-grained Vision-language Pre-training for Enhanced CT Image Understanding
by: Shui, Zhongyi, et al.
Published: (2025)

FOCUS: Fine-grained Optimization with Semantic Guided Understanding for Pedestrian Attributes Recognition
by: An, Hongyan, et al.
Published: (2025)

Data-free Knowledge Distillation for Fine-grained Visual Categorization
by: Shao, Renrong, et al.
Published: (2024)

DynFocus: Dynamic Cooperative Network Empowers LLMs with Video Understanding
by: Han, Yudong, et al.
Published: (2024)

HiRes-LLaVA: Restoring Fragmentation Input in High-Resolution Large Vision-Language Models
by: Huang, Runhui, et al.
Published: (2024)

Skim then Focus: Integrating Contextual and Fine-grained Views for Repetitive Action Counting
by: Zhao, Zhengqi, et al.
Published: (2024)

VideoZoomer: Reinforcement-Learned Temporal Focusing for Long Video Reasoning
by: Ding, Yang, et al.
Published: (2025)

VideoExpert: Augmented LLM for Temporal-Sensitive Video Understanding
by: Zhao, Henghao, et al.
Published: (2025)

FocusDiT: Masking Queries in Diffusion Transformers for Fine-grained Image Generation
by: Fang, Xueji, et al.
Published: (2026)

From Summary to Action: Enhancing Large Language Models for Complex Tasks with Open World APIs
by: Liu, Yulong, et al.
Published: (2024)

T2SGrid: Temporal-to-Spatial Gridification for Video Temporal Grounding
by: Guo, Chaohong, et al.
Published: (2026)

PanGu-Draw: Advancing Resource-Efficient Text-to-Image Synthesis with Time-Decoupled Training and Reusable Coop-Diffusion
by: Lu, Guansong, et al.
Published: (2023)

FriendsQA: A New Large-Scale Deep Video Understanding Dataset with Fine-grained Topic Categorization for Story Videos
by: Wu, Zhengqian, et al.
Published: (2024)

VideoRefer Suite: Advancing Spatial-Temporal Object Understanding with Video LLM
by: Yuan, Yuqian, et al.
Published: (2024)

FC-VFI: Faithful and Consistent Video Frame Interpolation for High-FPS Slow Motion Video Generation
by: Ding, Ganggui, et al.
Published: (2026)

LION-FS: Fast & Slow Video-Language Thinker as Online Video Assistant
by: Li, Wei, et al.
Published: (2025)

VTG-LLM: Integrating Timestamp Knowledge into Video LLMs for Enhanced Video Temporal Grounding
by: Guo, Yongxin, et al.
Published: (2024)

Caption Anything in Video: Fine-grained Object-centric Captioning via Spatiotemporal Multimodal Prompting
by: Tang, Yunlong, et al.
Published: (2025)