7 papers
Diffusion Models for Image Restoration and Enhancement: A Comprehensive Survey
Xin Li, Yulin Ren, Xin Jin +5
Image restoration (IR) has been an indispensable and challenging task in the low-level vision field, which strives to improve the subjective quality of images distorted by various…
InceptionNeXt: When Inception Meets ConvNeXt
Weihao Yu, Pan Zhou, Shuicheng Yan +1
Inspired by the long-range modeling ability of ViTs, large-kernel convolutions are widely studied and adopted recently to enlarge the receptive field and improve model performance,…
GFlow: Recovering 4D World from Monocular Video
Shizun Wang, Xingyi Yang, Qiuhong Shen +2
Recovering 4D world from monocular video is a crucial yet challenging task. Conventional methods usually rely on the assumptions of multi-view videos, known camera parameters, or s…
MVGamba: Unify 3D Content Generation as State Space Sequence Modeling
Xuanyu Yi, Zike Wu, Qiuhong Shen +6
Recent 3D large reconstruction models (LRMs) can generate high-quality 3D content in sub-seconds by integrating multi-view diffusion models with scalable multi-view reconstructors.…
MM-Vet v2: A Challenging Benchmark to Evaluate Large Multimodal Models for Integrated Capabilities
Weihao Yu, Zhengyuan Yang, Lingfeng Ren +7
MM-Vet, with open-ended vision-language questions targeting at evaluating integrated capabilities, has become one of the most popular benchmarks for large multimodal model evaluati…
MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities
Weihao Yu, Zhengyuan Yang, Linjie Li +5
We propose MM-Vet, an evaluation benchmark that examines large multimodal models (LMMs) on complicated multimodal tasks. Recent LMMs have shown various intriguing abilities, such a…