342 citations · 1.8k across the 90 of their papers we have counts for
80 papers · 1 filter
DUET-VLM: Dual stage Unified Efficient Token reduction for VLM Training and Inference
Aditya Kumar Singh, Hitesh Kandala, Pratik Prabhanjan Brahma +2
Vision-language models (VLMs) have achieved remarkable multimodal understanding and reasoning capabilities, yet remain computationally expensive due to dense visual tokenization. E…
EgoGroups: A Benchmark For Detecting Social Groups of People in the Wild
Jeffri Murrugarra-Llerena, Pranav Chitale, Zicheng Liu +4
Social group detection, or the identification of humans involved in reciprocal interpersonal interactions (e.g., family members, friends, and customers and merchants), is a crucial…
ORES: Open-vocabulary Responsible Visual Synthesis
Minheng Ni, Chenfei Wu, Xiaodong Wang +4
Avoiding synthesizing specific visual concepts is an essential challenge in responsible visual synthesis. However, the visual concept that needs to be avoided for responsible visua…
Spatial-Frequency U-Net for Denoising Diffusion Probabilistic Models
Xin Yuan, Linjie Li, Jianfeng Wang +4
In this paper, we study the denoising diffusion probabilistic model (DDPM) in wavelet space, instead of pixel space, for visual synthesis. Considering the wavelet transform represe…
DisCo: Disentangled Control for Realistic Human Dance Generation
Tan Wang, Linjie Li, Kevin Lin +6
Generative AI has made significant strides in computer vision, particularly in text-driven image/video synthesis (T2I/T2V). Despite the notable advancements, it remains challenging…
RefineVIS: Video Instance Segmentation with Temporal Attention Refinement
Andre Abrantes, Jiang Wang, Peng Chu +2
We introduce a novel framework called RefineVIS for Video Instance Segmentation (VIS) that achieves good object association between frames and accurate segmentation masks by iterat…
PaintSeg: Training-free Segmentation via Painting
Xiang Li, Chung-Ching Lin, Yinpeng Chen +3
The paper introduces PaintSeg, a new unsupervised method for segmenting objects without any training. We propose an adversarial masked contrastive painting (AMCP) process, which cr…
Neural Voting Field for Camera-Space 3D Hand Pose Estimation
Lin Huang, Chung-Ching Lin, Kevin Lin +4
We present a unified framework for camera-space 3D hand pose estimation from a single RGB image based on 3D implicit representation. As opposed to recent works, most of which first…
Image as First-Order Norm+Linear Autoregression: Unveiling Mathematical Invariance
Yinpeng Chen, Xiyang Dai, Dongdong Chen +4
This paper introduces a novel mathematical property applicable to diverse images, referred to as FINOLA (First-Order Norm+Linear Autoregressive). FINOLA represents each image in th…
Adaptive Human Matting for Dynamic Videos
Chung-Ching Lin, Jiang Wang, Kun Luo +4
The most recent efforts in video matting have focused on eliminating trimap dependency since trimap annotations are expensive and trimap-based methods are less adaptable for real-t…
Binary Latent Diffusion
Ze Wang, Jiang Wang, Zicheng Liu +1
In this paper, we show that a binary latent space can be explored for compact yet expressive image representations. We model the bi-directional mappings between an image and the co…
NUWA-XL: Diffusion over Diffusion for eXtremely Long Video Generation
Shengming Yin, Chenfei Wu, Huan Yang +13
In this paper, we propose NUWA-XL, a novel Diffusion over Diffusion architecture for eXtremely Long video generation. Most current work generates long videos segment by segment seq…
MM-REACT: Prompting ChatGPT for Multimodal Reasoning and Action
Zhengyuan Yang, Linjie Li, Jianfeng Wang +7
We propose MM-REACT, a system paradigm that integrates ChatGPT with a pool of vision experts to achieve multimodal reasoning and action. In this paper, we define and explore a comp…
Equivariant Similarity for Vision-Language Foundation Models
Tan Wang, Kevin Lin, Linjie Li +5
This study explores the concept of equivariance in vision-language foundation models (VLMs), focusing specifically on the multimodal similarity function that is not only the major…
Layer Grafted Pre-training: Bridging Contrastive Learning And Masked Image Modeling For Label-Efficient Representations
Ziyu Jiang, Yinpeng Chen, Mengchen Liu +5
Recently, both Contrastive Learning (CL) and Mask Image Modeling (MIM) demonstrate that self-supervision is powerful to learn good representations. However, naively combining them…
Learning 3D Photography Videos via Self-supervised Diffusion on Single Images
Xiaodong Wang, Chenfei Wu, Shengming Yin +9
3D photography renders a static image into a video with appealing 3D visual effects. Existing approaches typically first conduct monocular depth estimation, then render the input f…
Energy-Inspired Self-Supervised Pretraining for Vision Models
Ze Wang, Jiang Wang, Zicheng Liu +1
Motivated by the fact that forward and backward passes of a deep network naturally form symmetric mappings between input and output representations, we introduce a simple yet effec…
Exploring Discrete Diffusion Models for Image Captioning
Zixin Zhu, Yixuan Wei, Jianfeng Wang +7
The image captioning task is typically realized by an auto-regressive method that decodes the text tokens one by one. We present a diffusion-based captioning model, dubbed the name…
GRiT: A Generative Region-to-text Transformer for Object Understanding
Jialian Wu, Jianfeng Wang, Zhengyuan Yang +4
This paper presents a Generative RegIon-to-Text transformer, GRiT, for object understanding. The spirit of GRiT is to formulate object understanding as <region, text> pairs, where…
ReCo: Region-Controlled Text-to-Image Generation
Zhengyuan Yang, Jianfeng Wang, Zhe Gan +8
Recently, large-scale text-to-image (T2I) models have shown impressive performance in generating high-fidelity images, but with limited controllability, e.g., precisely specifying…
Self-Supervised Learning based on Heat Equation
Yinpeng Chen, Xiyang Dai, Dongdong Chen +4
This paper presents a new perspective of self-supervised learning based on extending heat equation into high dimensional feature space. In particular, we remove time dependence by…
MPT: Mesh Pre-Training with Transformers for Human Pose and Mesh Reconstruction
Kevin Lin, Chung-Ching Lin, Lin Liang +2
Traditional methods of reconstructing 3D human pose and mesh from single images rely on paired image-mesh datasets, which can be difficult and expensive to obtain. Due to this limi…
MogaNet: Multi-order Gated Aggregation Network
Siyuan Li, Zedong Wang, Zicheng Liu +6
By contextualizing the kernel as global as possible, Modern ConvNets have shown great potential in computer vision tasks. However, recent progress on multi-order game-theoretic int…
Vision-Language Pre-training: Basics, Recent Advances, and Future Trends
Zhe Gan, Linjie Li, Chunyuan Li +3
This paper surveys vision-language pre-training (VLP) methods for multimodal intelligence that have been developed in the last few years. We group these approaches into three categ…