5 papers
From SRA to Self-Flow: Data Augmentation or Self-Supervision?
Dengyang Jiang, Mengmeng Wang, Harry Yang +1
Representation alignment has become an effective way to accelerate diffusion transformer training and improve generation quality. Recent self-alignment methods, such as SRA and Sel…
Distribution Matching Distillation Meets Reinforcement Learning
Dengyang Jiang, Dongyang Liu, Zanyi Wang +12
Distribution Matching Distillation (DMD) facilitates efficient inference by distilling multi-step diffusion models into few-step variants. Concurrently, Reinforcement Learning (RL)…
Deforming Videos to Masks: Flow Matching for Referring Video Segmentation
Zanyi Wang, Dengyang Jiang, Liuzhuozheng Li +6
Referring Video Object Segmentation (RVOS) requires segmenting specific objects in a video guided by a natural language description. The core challenge of RVOS is to anchor abstrac…
AffordanceSAM: Segment Anything Once More in Affordance Grounding
Dengyang Jiang, Zanyi Wang, Hengzhuang Li +7
Building a generalized affordance grounding model to identify actionable regions on objects is vital for real-world applications. Existing methods to train the model can be divided…
Low-rank SIFT: An Affine Invariant Feature for Place Recognition
Chao Yang, Shengnan Caih, Jingdong Wang +1
In this paper, we present a novel affine-invariant feature based on SIFT, leveraging the regular appearance of man-made objects. The feature achieves full affine invariance without…