10 citations · 20 across the 9 of their papers we have counts for
10 papers
FDSG: Forecasting Dynamic Scene Graphs
Yi Yang, Yuren Cong, Hao Cheng +2
Dynamic scene graph generation extends scene graph generation from images to videos by modeling entity relationships and their temporal evolution. However, existing methods either…
WorldAfford: Affordance Grounding based on Natural Language Instructions
Changmao Chen, Yuren Cong, Zhen Kan
Affordance grounding aims to localize the interaction regions for the manipulated objects in the scene image according to given instructions. A critical challenge in affordance gro…
Segment Any Object Model (SAOM): Real-to-Simulation Fine-Tuning Strategy for Multi-Class Multi-Instance Segmentation
Mariia Khan, Yue Qiu, Yuren Cong +3
Multi-class multi-instance segmentation is the task of identifying masks for multiple object classes and multiple instances of the same class within an image. The foundational Segm…
FLATTEN: optical FLow-guided ATTENtion for consistent text-to-video editing
Yuren Cong, Mengmeng Xu, Christian Simon +7
Text-to-video editing aims to edit the visual appearance of a source video conditional on textual prompts. A major challenge in this task is to ensure that all frames in the edited…
SPAN: Learning Similarity between Scene Graphs and Images with Transformers
Yuren Cong, Wentong Liao, Bodo Rosenhahn +1
Learning similarity between scene graphs and images aims to estimate a similarity score given a scene graph and an image. There is currently no research dedicated to this task, alt…
Attribute-Centric Compositional Text-to-Image Generation
Yuren Cong, Martin Renqiang Min, Li Erran Li +2
Despite the recent impressive breakthroughs in text-to-image generation, generative models have difficulty in capturing the data distribution of underrepresented attribute composit…
SSGVS: Semantic Scene Graph-to-Video Synthesis
Yuren Cong, Jinhui Yi, Bodo Rosenhahn +1
As a natural extension of the image synthesis task, video synthesis has attracted a lot of interest recently. Many image synthesis works utilize class labels or text as guidance. H…
RelTR: Relation Transformer for Scene Graph Generation
Yuren Cong, Michael Ying Yang, Bodo Rosenhahn
Different objects in the same scene are more or less related to each other, but only a limited number of these relationships are noteworthy. Inspired by DETR, which excels in objec…
Spatial-Temporal Transformer for Dynamic Scene Graph Generation
Yuren Cong, Wentong Liao, Hanno Ackermann +2
Dynamic scene graph generation aims at generating a scene graph of the given video. Compared to the task of scene graph generation from images, it is more challenging because of th…
NODIS: Neural Ordinary Differential Scene Understanding
Cong Yuren, Hanno Ackermann, Wentong Liao +2
Semantic image understanding is a challenging topic in computer vision. It requires to detect all objects in an image, but also to identify all the relations between them. Detected…