794 citations · 4.8k across the 152 of their papers we have counts for
154 papers
LAVIE: High-Quality Video Generation with Cascaded Latent Diffusion Models
Yaohui Wang, Xinyuan Chen, Xin Ma +17
This work aims to learn a high-quality text-to-video (T2V) generative model by leveraging a pre-trained text-to-image (T2I) model as a basis. It is a highly desirable yet challengi…
Semantics Meets Temporal Correspondence: Self-supervised Object-centric Learning in Videos
Rui Qian, Shuangrui Ding, Xian Liu +1
Self-supervised methods have shown remarkable progress in learning high-level semantics and low-level temporal correspondence. Building on these results, we take one step further a…
CLEVA: Chinese Language Models EVAluation Platform
Yanyang Li, Jianqiao Zhao, Duo Zheng +8
With the continuous emergence of Chinese Large Language Models (LLMs), how to evaluate a model's capabilities has become an increasingly significant issue. The absence of a compreh…
Learning Referring Video Object Segmentation from Weak Annotation
Wangbo Zhao, Kepan Nan, Songyang Zhang +3
Referring video object segmentation (RVOS) is a task that aims to segment the target object in all video frames based on a sentence describing the object. Although existing RVOS me…
Improving Pixel-based MIM by Reducing Wasted Modeling Capability
Yuan Liu, Songyang Zhang, Jiacheng Chen +3
There has been significant progress in Masked Image Modeling (MIM). Existing MIM methods can be broadly categorized into two groups based on the reconstruction target: pixel-based…
DNA-Rendering: A Diverse Neural Actor Repository for High-Fidelity Human-centric Rendering
Wei Cheng, Ruixiang Chen, Wanqi Yin +18
Realistic human-centric rendering plays a key role in both computer vision and computer graphics. Rapid progress has been made in the algorithm aspect over the years, yet existing…
MMBench: Is Your Multi-modal Model an All-around Player?
Yuan Liu, Haodong Duan, Yuanhan Zhang +9
Large vision-language models (VLMs) have recently achieved remarkable progress, exhibiting impressive multimodal perception and reasoning abilities. However, effectively evaluating…
AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning
Yuwei Guo, Ceyuan Yang, Anyi Rao +6
With the advance of text-to-image (T2I) diffusion models (e.g., Stable Diffusion) and corresponding personalization techniques such as DreamBooth and LoRA, everyone can manifest th…
Scene as Occupancy
Chonghao Sima, Wenwen Tong, Tai Wang +8
Human driver can easily describe the complex traffic scene by visual system. Such an ability of precise perception is essential for driver's planning. To achieve this, a geometry-a…
HireVAE: An Online and Adaptive Factor Model Based on Hierarchical and Regime-Switch VAE
Zikai Wei, Anyi Rao, Bo Dai +1
Factor model is a fundamental investment tool in quantitative investment, which can be empowered by deep learning to become more flexible and efficient in practical complicated inv…
Proteus: Simulating the Performance of Distributed DNN Training
Jiangfei Duan, Xiuhong Li, Ping Xu +4
DNN models are becoming increasingly larger to achieve unprecedented accuracy, and the accompanying increased computation and memory requirements necessitate the employment of mass…
E2EAI: End-to-End Deep Learning Framework for Active Investing
Zikai Wei, Bo Dai, Dahua Lin
Active investing aims to construct a portfolio of assets that are believed to be relatively profitable in the markets, with one popular method being to construct a portfolio via fa…
RenderMe-360: A Large Digital Asset Library and Benchmarks Towards High-fidelity Head Avatars
Dongwei Pan, Long Zhuo, Jingtan Piao +13
Synthesizing high-fidelity head avatars is a central problem for computer vision and graphics. While head avatar synthesis algorithms have advanced rapidly, the best ones still fac…
DORT: Modeling Dynamic Objects in Recurrent for Multi-Camera 3D Object Detection and Tracking
Qing Lian, Tai Wang, Dahua Lin +1
Recent multi-camera 3D object detectors usually leverage temporal information to construct multi-view stereo that alleviates the ill-posed depth estimation. However, they typically…
RIFormer: Keep Your Vision Backbone Effective While Removing Token Mixer
Jiahao Wang, Songyang Zhang, Yong Liu +6
This paper studies how to keep a vision backbone effective while removing token mixers in its basic building blocks. Token mixers, as self-attention for vision transformers (ViTs),…
V3Det: Vast Vocabulary Visual Detection Dataset
Jiaqi Wang, Pan Zhang, Tao Chu +6
Recent advances in detecting arbitrary objects in the real world are trained and evaluated on object detection datasets with a relatively restricted vocabulary. To facilitate the d…
Grid-guided Neural Radiance Fields for Large Urban Scenes
Linning Xu, Yuanbo Xiangli, Sida Peng +5
Purely MLP-based neural radiance fields (NeRF-based methods) often suffer from underfitting with blurred renderings on large-scale scenes due to limited model capacity. Recent appr…
AssetField: Assets Mining and Reconfiguration in Ground Feature Plane Representation
Yuanbo Xiangli, Linning Xu, Xingang Pan +3
Both indoor and outdoor environments are inherently structured and repetitive. Traditional modeling pipelines keep an asset library storing unique object templates, which is both v…
PixMIM: Rethinking Pixel Reconstruction in Masked Image Modeling
Yuan Liu, Songyang Zhang, Jiacheng Chen +2
Masked Image Modeling (MIM) has achieved promising progress with the advent of Masked Autoencoders (MAE) and BEiT. However, subsequent works have complicated the framework with new…
MV-JAR: Masked Voxel Jigsaw and Reconstruction for LiDAR-Based Self-Supervised Pre-Training
Runsen Xu, Tai Wang, Wenwei Zhang +4
This paper introduces the Masked Voxel Jigsaw and Reconstruction (MV-JAR) method for LiDAR-based self-supervised pre-training and a carefully designed data-efficient 3D object dete…
Position-Guided Point Cloud Panoptic Segmentation Transformer
Zeqi Xiao, Wenwei Zhang, Tai Wang +3
DEtection TRansformer (DETR) started a trend that uses a group of learnable queries for unified visual perception. This work begins by applying this appealing paradigm to LiDAR-bas…
Controllable Mesh Generation Through Sparse Latent Point Diffusion Models
Zhaoyang Lyu, Jinyi Wang, Yuwei An +3
Mesh generation is of great value in various applications involving computer graphics and virtual content, yet designing generative models for meshes is challenging due to their ir…
SynBody: Synthetic Dataset with Layered Human Models for 3D Human Perception and Modeling
Zhitao Yang, Zhongang Cai, Haiyi Mei +12
Synthetic data has emerged as a promising source for 3D human research as it offers low-cost access to large-scale human datasets. To advance the diversity and annotation quality o…
Semi-Supervised Semantic Segmentation via Gentle Teaching Assistant
Ying Jin, Jiaqi Wang, Dahua Lin
Semi-Supervised Semantic Segmentation aims at training the segmentation model with limited labeled data and a large amount of unlabeled data. To effectively leverage the unlabeled…