14 citations · 21 across the 13 of their papers we have counts for
14 papers
ReDraft, Don't Just Distill: Reference-Driven Revision for Continual VLLM Post-Training
Zhihao Zhang, Mingqi Wu, Qiaole Dong +15
Continual post-training of large multimodal models should add new capabilities while preserving those from pre-training, and the two goals pull in opposite directions. SFT gives ex…
Enhancing Video Inpainting with Aligned Frame Interval Guidance
Ming Xie, Junqiu Yu, Qiaole Dong +2
Recent image-to-video (I2V) based video inpainting methods have made significant strides by leveraging single-image priors and modeling temporal consistency across masked frames. N…
PPMStereo: Pick-and-Play Memory Construction for Consistent Dynamic Stereo Matching
Yun Wang, Junjie Hu, Qiaole Dong +4
Temporally consistent depth estimation from stereo video is critical for real-world applications such as augmented reality, where inconsistent depth estimation disrupts the immersi…
Reasoning or Memorization? Unreliable Results of Reinforcement Learning Due to Data Contamination
Mingqi Wu, Zhihao Zhang, Qiaole Dong +11
Reasoning in large language models has long been a central research focus, and recent studies employing reinforcement learning (RL) have introduced diverse methods that yield subst…
Why Reinforcement Fine-Tuning Enables MLLMs Preserve Prior Knowledge Better: A Data Perspective
Zhihao Zhang, Qiaole Dong, Qi Zhang +12
Post-training algorithms such as Supervised Fine-Tuning (SFT) and Reinforcement Fine-Tuning (RFT) are widely used to adapt (multimodal) large language models to downstream tasks. W…
Online Dense Point Tracking with Streaming Memory
Qiaole Dong, Yanwei Fu
Dense point tracking is a challenging task requiring the continuous tracking of every point in the initial frame throughout a substantial portion of a video, even in the presence o…
MemFlow: Optical Flow Estimation and Prediction with Memory
Qiaole Dong, Yanwei Fu
Optical flow is a classical task that is important to the vision community. Classical optical flow estimation uses two frames as input, whilst some recent methods consider multiple…
Repositioning the Subject within Image
Yikai Wang, Chenjie Cao, Ke Fan +4
Current image manipulation primarily centers on static manipulation, such as replacing specific regions within an image or altering its overall style. In this paper, we introduce a…
Open-DDVM: A Reproduction and Extension of Diffusion Model for Optical Flow Estimation
Qiaole Dong, Bo Zhao, Yanwei Fu
Recently, Google proposes DDVM which for the first time demonstrates that a general diffusion model for image-to-image translation task works impressively well on optical flow esti…
LeftRefill: Filling Right Canvas based on Left Reference through Generalized Text-to-Image Diffusion Model
Chenjie Cao, Yunuo Cai, Qiaole Dong +2
This paper introduces LeftRefill, an innovative approach to efficiently harness large Text-to-Image (T2I) diffusion models for reference-guided image synthesis. As the name implies…
Rethinking Optical Flow from Geometric Matching Consistent Perspective
Qiaole Dong, Chenjie Cao, Yanwei Fu
Optical flow estimation is a challenging problem remaining unsolved. Recent deep learning based optical flow models have achieved considerable success. However, these models often…
ZITS++: Image Inpainting by Improving the Incremental Transformer on Structural Priors
Chenjie Cao, Qiaole Dong, Yanwei Fu
Image inpainting involves filling missing areas of a corrupted image. Despite impressive results have been achieved recently, restoring images with both vivid textures and reasonab…
Learning Prior Feature and Attention Enhanced Image Inpainting
Chenjie Cao, Qiaole Dong, Yanwei Fu
Many recent inpainting works have achieved impressive results by leveraging Deep Neural Networks (DNNs) to model various prior information for image restoration. Unfortunately, the…
Incremental Transformer Structure Enhanced Image Inpainting with Masking Positional Encoding
Qiaole Dong, Chenjie Cao, Yanwei Fu
Image inpainting has made significant advances in recent years. However, it is still challenging to recover corrupted images with both vivid textures and reasonable structures. Som…