1 citations · 2 across the 9 of their papers we have counts for
10 papers
VideoJev: System One Model for Video Understanding and Interaction
Yuhan Zhu, Xiangyu Zeng, Qingyi Si +15
Visual agents must turn video observations into timely decisions to track progress and choose what to do next. Building on the emerging System One paradigm, we introduce VideoJev,…
Uni-ViGU: Towards Unified Video Generation and Understanding via A Diffusion-Based Video Generator
Luozheng Qin, Jia Gong, Qian Qiao +6
Unified multimodal models integrating visual understanding and generation face a fundamental challenge: visual generation incurs substantially higher computational costs than under…
Omni-Video 2: Scaling MLLM-Conditioned Diffusion for Unified Video Generation and Editing
Hao Yang, Zhiyu Tan, Jia Gong +7
We present Omni-Video 2, a scalable and computationally efficient model that connects pretrained multimodal large-language models (MLLMs) with video diffusion models for unified vi…
Uni-cot: Towards Unified Chain-of-Thought Reasoning Across Text and Vision
Luozheng Qin, Jia Gong, Yuqing Sun +6
Chain-of-Thought (CoT) reasoning has been widely adopted to enhance Large Language Models (LLMs) by decomposing complex tasks into simpler, sequential subtasks. However, extending…
Omni-Video: Democratizing Unified Video Understanding and Generation
Zhiyu Tan, Hao Yang, Luozheng Qin +3
Notable breakthroughs in unified understanding and generation modeling have led to remarkable advancements in image understanding, reasoning, production and editing, yet current fo…
Cockatiel: Ensembling Synthetic and Human Preferenced Training for Detailed Video Caption
Luozheng Qin, Zhiyu Tan, Mengping Yang +2
Video Detailed Captioning (VDC) is a crucial task for vision-language bridging, enabling fine-grained descriptions of complex video content. In this paper, we first comprehensively…
Raccoon: Multi-stage Diffusion Training with Coarse-to-Fine Curating Videos
Zhiyu Tan, Junyan Wang, Hao Yang +4
Text-to-video generation has demonstrated promising progress with the advent of diffusion models, yet existing approaches are limited by dataset quality and computational resources…
VidGen-1M: A Large-Scale Dataset for Text-to-video Generation
Zhiyu Tan, Xiaomeng Yang, Luozheng Qin +1
The quality of video-text pairs fundamentally determines the upper bound of text-to-video models. Currently, the datasets used for training these models suffer from significant sho…
EVALALIGN: Supervised Fine-Tuning Multimodal LLMs with Human-Aligned Data for Evaluating Text-to-Image Models
Zhiyu Tan, Xiaomeng Yang, Luozheng Qin +3
The recent advancements in text-to-image generative models have been remarkable. Yet, the field suffers from a lack of evaluation metrics that accurately reflect the performance of…
An Empirical Study and Analysis of Text-to-Image Generation Using Large Language Model-Powered Textual Representation
Zhiyu Tan, Mengping Yang, Luozheng Qin +5
One critical prerequisite for faithful text-to-image generation is the accurate understanding of text inputs. Existing methods leverage the text encoder of the CLIP model to repres…