5 citations · 5 across the 6 of their papers we have counts for
5 papers · 1 filter
Can We Build Scene Graphs, Not Classify Them? FlowSG: Progressive Image-Conditioned Scene Graph Generation with Flow Matching
Xin Hu, Ke Qin, Wen Yin +3
Scene Graph Generation (SGG) unifies object localization and visual relationship reasoning by predicting boxes and subject-predicate-object triples. Yet most pipelines treat SGG as…
Fixed Anchors Are Not Enough: Dynamic Retrieval and Persistent Homology for Dataset Distillation
Muquan Li, Hang Gou, Yingyi Ma +3
Decoupled dataset distillation (DD) compresses large corpora into a few synthetic images by matching a frozen teacher's statistics. However, current residual-matching pipelines rel…
Towards Effective Data-Free Knowledge Distillation via Diverse Diffusion Augmentation
Muquan Li, Dongyang Zhang, Tao He +3
Data-free knowledge distillation (DFKD) has emerged as a pivotal technique in the domain of model compression, substantially reducing the dependency on the original training data.…
Towards Lifelong Scene Graph Generation with Knowledge-ware In-context Prompt Learning
Tao He, Tongtong Wu, Dongyang Zhang +3
Scene graph generation (SGG) endeavors to predict visual relationships between pairs of objects within an image. Prevailing SGG methods traditionally assume a one-off learning proc…
Towards a Unified Transformer-based Framework for Scene Graph Generation and Human-object Interaction Detection
Tao He, Lianli Gao, Jingkuan Song +1
Scene graph generation (SGG) and human-object interaction (HOI) detection are two important visual tasks aiming at localising and recognising relationships between objects, and int…