3 citations · 5 across the 8 of their papers we have counts for
9 papers · 1 filter
PixelDense: Dense Prediction as Representation Alignment for Pixel Diffusion
Lehan Yang, Daiqing Qi, Wenhao Zhang +9
Representation alignment (REPA) accelerates diffusion transformer training, but its alignment targets are almost exclusively semantic encoders such as DINOv2 and CLIP. Recent analy…
DMA: Pixel-space Distribution Matching with Adversarial and Anchor Losses
Xin Lin, Zhifei Zhang, Yuqian Zhou +6
Distribution matching distillation (DMD) provides a general framework for few-step diffusion generation, but its modern text-to-image instantiations have been developed primarily a…
Unified Dense Prediction of Video Diffusion
Lehan Yang, Lu Qi, Xiangtai Li +3
We present a unified network for simultaneously generating videos and their corresponding entity segmentation and depth maps from text prompts. We utilize colormap to represent ent…
VRMDiff: Text-Guided Video Referring Matting Generation of Diffusion
Lehan Yang, Jincen Song, Tianlong Wang +4
We propose a new task, video referring matting, which obtains the alpha matte of a specified instance by inputting a referring caption. We treat the dense prediction task of mattin…
The Ninth NTIRE 2024 Efficient Super-Resolution Challenge Report
Bin Ren, Yawei Li, Nancy Mehta +129
This paper provides a comprehensive review of the NTIRE 2024 challenge, focusing on efficient single-image super-resolution (ESR) solutions and their outcomes. The task of this cha…
High-Quality Entity Segmentation and Grounding
Lu Qi, Yi-Wen Chen, Tao Zhang +4
In this work, we propose ESG, a pipeline for high-quality entity segmentation and grounding supported by a new dataset EntitySeg. At first, the proposed dataset naming EntitySeg co…
UniGS: Unified Representation for Image Generation and Segmentation
Lu Qi, Lehan Yang, Weidong Guo +4
This paper introduces a novel unified representation of diffusion models for image generation and segmentation. Specifically, we use a colormap to represent entity-level masks, add…
Rethinking the Knowledge Distillation From the Perspective of Model Calibration
Lehan Yang, Jincen Song
Recent years have witnessed dramatically improvements in the knowledge distillation, which can generate a compact student model for better efficiency while retaining the model effe…
NTIRE 2021 Multi-modal Aerial View Object Classification Challenge
Jerrick Liu, Nathan Inkawhich, Oliver Nina +30
In this paper, we introduce the first Challenge on Multi-modal Aerial View Object Classification (MAVOC) in conjunction with the NTIRE 2021 workshop at CVPR. This challenge is comp…