11 citations · 11 across the 13 of their papers we have counts for
14 papers · 1 filter
Open-o3-Video-v2: Seek, Ground, and Reason with Verifiable Spatio-Temporal Evidence
Jiahao Meng, Zhongyuan Bao, Yue Tan +7
Reliable video reasoning requires models to produce correct answers and expose supporting visual evidence. Open-o3-Video enables verifiable reasoning by embedding timestamps and ob…
UniSHARP: Universal Sharp Monocular View Synthesis
Meixi Song, Dizhe Zhang, Hao Ren +4
In this work, we focus on extending SHARP, the popular photorealistic view synthesis method, for universal monocular rendering across a continuum of camera systems, from convention…
Watch, Remember, Reason: Human-View Video Understanding with MLLMs
Jiahao Meng, Yue Tan, Qi Xu +12
Video understanding is being rapidly transformed by multimodal large language models (MLLMs), as research moves from short clips to long, multimodal, and knowledge-intensive video…
AlbumFill: Album-Guided Reasoning and Retrieval for Personalized Image Completion
Yu-Ju Tsai, Brian Price, Qing Liu +5
Personalized image completion aims to restore occluded regions in personal photos while preserving identity and appearance. Existing methods either rely on generic inpainting model…
Towards High Fidelity Face Swapping: A Comprehensive Survey and New Benchmark
Qi Li, Weining Wang, Shuangjun Du +5
Face swapping has witnessed significant progress in recent years, largely driven by advances in deep generative models such as GANs and diffusion models.Despite these advances, exi…
Streaming Autoregressive Video Generation via Diagonal Distillation
Jinxiu Liu, Xuanming Liu, Kangfu Mei +3
Large pretrained diffusion models have significantly enhanced the quality of generated videos, and yet their use in real-time streaming remains limited. Autoregressive models offer…
FaceCam: Portrait Video Camera Control via Scale-Aware Conditioning
Weijie Lyu, Ming-Hsuan Yang, Zhixin Shu
We introduce FaceCam, a system that generates video under customizable camera trajectories for monocular human portrait video input. Recent camera control approaches based on large…
Towards Affordance-Aware Articulation Synthesis for Rigged Objects
Yu-Chu Yu, Chieh Hubert Lin, Hsin-Ying Lee +3
Rigged objects are commonly used in artist pipelines, as they can flexibly adapt to different scenes and postures. However, articulating the rigs into realistic affordance-aware po…
Taming Latent Diffusion Model for Neural Radiance Field Inpainting
Chieh Hubert Lin, Changil Kim, Jia-Bin Huang +5
Neural Radiance Field (NeRF) is a representation for 3D reconstruction from multi-view images. Despite some recent work showing preliminary success in editing a reconstructed NeRF…
Panda-70M: Captioning 70M Videos with Multiple Cross-Modality Teachers
Tsai-Shien Chen, Aliaksandr Siarohin, Willi Menapace +8
The quality of the data and annotation upper-bounds the quality of a downstream model. While there exist large text corpora and image-text pairs, high-quality video-text data is mu…
Towards 4D Human Video Stylization
Tiantian Wang, Xinxin Zuo, Fangzhou Mu +2
We present a first step towards 4D (3D and time) human video stylization, which addresses style transfer, novel view synthesis and human animation within a unified framework. While…
Exploiting Diffusion Prior for Generalizable Dense Prediction
Hsin-Ying Lee, Hung-Yu Tseng, Ming-Hsuan Yang
Contents generated by recent advanced Text-to-Image (T2I) diffusion models are sometimes too imaginative for existing off-the-shelf dense predictors to estimate due to the immitiga…
One-for-All: Towards Universal Domain Translation with a Single StyleGAN
Yong Du, Jiahui Zhan, Xinzhe Li +4
In this paper, we propose a novel translation model, UniTranslator, for transforming representations between visually distinct domains under conditions of limited training data and…
Learning Disentangled Representation for One-shot Progressive Face Swapping
Qi Li, Weining Wang, Chengzhong Xu +2
Although face swapping has attracted much attention in recent years, it remains a challenging problem. Existing methods leverage a large number of data samples to explore the intri…