Opus AI Research is the research division of OpusClip, dedicated to advancing artificial intelligence technologies, particularly in video understanding. Our team has contributed numerous high-impact publications in top-tier conferences and journals, covering areas such as video editing, generative models, and few-shot learning. Additionally, we actively participate in international AI competitions, achieving top rankings in video understanding challenges.
Title | Conference |
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RSVP: Reasoning Segmentation via Visual Prompting and Multi-modal Chain-of-Thought | ACL 2025 Main |
VEU-Bench: Towards Comprehensive Understanding of Video Editing | CVPR 2025 Highlight |
Number it: Temporal Grounding Videos like Flipping Manga | CVPR 2025 Poster |
Video Repurposing from User Generated Content: A Large-scale Dataset and Benchmark | AAAI 2025 Poster |
Unlearning Concepts in Diffusion Model via Concept Domain Correction and Concept Preserving Gradient | AAAI 2025 Poster |
Envisioning Class Entity Reasoning by Large Language Models for Few-shot Learning | AAAI 2025 Poster |
Frame Order Matters: A Temporal Sequence-Aware Model for Few-Shot Action Recognition | AAAI 2025 Poster |
Object-Level Out-of-Distribution Detection via Regional Uncertainty Alignment of Multimodal Representations | AAAI 2025 Oral |
VisTa: Visual-contextual and Text-augmented Zero-shot Object-level OOD Detection | ICASSP 2025 Poster |
Cocktail: Chunk-Adaptive Mixed-Precision Quantization for Long-Context LLM Inference | DATE 2025 Best Paper |
Exploring Diverse In-Context Configurations for Image Caption | NeurIPS 2023 Poster |
Few-Shot Font Generation by Learning Fine-Grained Local Styles | CVPR 2022 Poster |
Exploiting Deep Cross-Slice Features From CT Images For Multi-Class Pneumonia Classification | ICIP 2021 Best Student Paper |
Fuzzy SLIC: Fuzzy Simple Linear Iterative Clustering | TCSVT 2020 |
Multilingual Video Reasoning Evaluation Challenge
Complex Video Reasoning & Robustness Evaluation Challenge
Multi-View Foul Recognition Track
Long-Term Video QA Track
Hour-Long Video QA Track
E-Commerce Debiasing Challenge