4 citations · 8 across the 18 of their papers we have counts for
10 papers · 1 filter
1.58-bit FLUX
Chenglin Yang, Celong Liu, Xueqing Deng +4
We present 1.58-bit FLUX, the first successful approach to quantizing the state-of-the-art text-to-image generation model, FLUX.1-dev, using 1.58-bit weights (i.e., values in {-1,…
FlowAR: Scale-wise Autoregressive Image Generation Meets Flow Matching
Sucheng Ren, Qihang Yu, Ju He +3
Autoregressive (AR) modeling has achieved remarkable success in natural language processing by enabling models to generate text with coherence and contextual understanding through…
ViCaS: A Dataset for Combining Holistic and Pixel-level Video Understanding using Captions with Grounded Segmentation
Ali Athar, Xueqing Deng, Liang-Chieh Chen
Recent advances in multimodal large language models (MLLMs) have expanded research in video understanding, primarily focusing on high-level tasks such as video captioning and quest…
Randomized Autoregressive Visual Generation
Qihang Yu, Ju He, Xueqing Deng +2
This paper presents Randomized AutoRegressive modeling (RAR) for visual generation, which sets a new state-of-the-art performance on the image generation task while maintaining ful…
MaskBit: Embedding-free Image Generation via Bit Tokens
Mark Weber, Lijun Yu, Qihang Yu +4
Masked transformer models for class-conditional image generation have become a compelling alternative to diffusion models. Typically comprising two stages - an initial VQGAN model…
An Image is Worth 32 Tokens for Reconstruction and Generation
Qihang Yu, Mark Weber, Xueqing Deng +3
Recent advancements in generative models have highlighted the crucial role of image tokenization in the efficient synthesis of high-resolution images. Tokenization, which transform…
Alleviating Distortion in Image Generation via Multi-Resolution Diffusion Models and Time-Dependent Layer Normalization
Qihao Liu, Zhanpeng Zeng, Ju He +3
This paper presents innovative enhancements to diffusion models by integrating a novel multi-resolution network and time-dependent layer normalization. Diffusion models have gained…
Enhancing Temporal Consistency in Video Editing by Reconstructing Videos with 3D Gaussian Splatting
Inkyu Shin, Qihang Yu, Xiaohui Shen +3
Recent advancements in zero-shot video diffusion models have shown promise for text-driven video editing, but challenges remain in achieving high temporal consistency. To address t…
COCONut: Modernizing COCO Segmentation
Xueqing Deng, Qihang Yu, Peng Wang +2
In recent decades, the vision community has witnessed remarkable progress in visual recognition, partially owing to advancements in dataset benchmarks. Notably, the established COC…
ViTamin: Designing Scalable Vision Models in the Vision-Language Era
Jieneng Chen, Qihang Yu, Xiaohui Shen +2
Recent breakthroughs in vision-language models (VLMs) start a new page in the vision community. The VLMs provide stronger and more generalizable feature embeddings compared to thos…