1 citations · 2 across the 10 of their papers we have counts for
11 papers
MEMOBench: A Process Level Memory Benchmark for Robotic Manipulation
Haiyang Sun, Haoxiao Wang, Junming Chen +6
Robotic manipulation often requires acting on information that is no longer visible, yet Vision-Language-Action policies are usually evaluated when the current observation largely…
Bridging the Pose-Semantic Gap: A Cascade Framework for Text-Based Person Anomaly Search
Zequn Xie, Guijin Luo, Chuxin Wang +4
Text-based person anomaly search retrieves specific behavioral events from surveillance archives using natural-language queries. Although recent pose-aware methods align geometric…
Diffusion Model as a Generalist Segmentation Learner
Haoxiao Wang, Antao Xiang, Haiyang Sun +8
Diffusion models are primarily trained for image synthesis, yet their denoising trajectories encode rich, spatially aligned visual priors. In this paper, we demonstrate that these…
From Perception to Planning: Evolving Ego-Centric Task-Oriented Spatiotemporal Reasoning via Curriculum Learning
Xiaoda Yang, Yuxiang Liu, Shenzhou Gao +8
Modern vision-language models achieve strong performance in static perception, but remain limited in the complex spatiotemporal reasoning required for embodied, egocentric tasks. A…
A Progressive Training Strategy for Embodied Vision-Language Models to Mitigate Spatio-Temporal Hallucinations
Xiaoda Yang, Shuai Yang, Can Wang +9
Vision-Language Models (VLMs) have made significant strides in static image understanding but continue to face critical hurdles in spatiotemporal reasoning. A major bottleneck is "…
WorldEdit: Towards Open-World Image Editing with a Knowledge-Informed Benchmark
Wang Lin, Feng Wang, Majun Zhang +7
Recent advances in image editing models have demonstrated remarkable capabilities in executing explicit instructions, such as attribute manipulation, style transfer, and pose synth…
IRBridge: Solving Image Restoration Bridge with Pre-trained Generative Diffusion Models
Hanting Wang, Tao Jin, Wang Lin +4
Bridge models in image restoration construct a diffusion process from degraded to clear images. However, existing methods typically require training a bridge model from scratch for…
Towards Transformer-Based Aligned Generation with Self-Coherence Guidance
Shulei Wang, Wang Lin, Hai Huang +8
We introduce a novel, training-free approach for enhancing alignment in Transformer-based Text-Guided Diffusion Models (TGDMs). Existing TGDMs often struggle to generate semantical…
Classifier-guided Gradient Modulation for Enhanced Multimodal Learning
Zirun Guo, Tao Jin, Jingyuan Chen +1
Multimodal learning has developed very fast in recent years. However, during the multimodal training process, the model tends to rely on only one modality based on which it could l…
Semantic Alignment for Multimodal Large Language Models
Tao Wu, Mengze Li, Jingyuan Chen +6
Research on Multi-modal Large Language Models (MLLMs) towards the multi-image cross-modal instruction has received increasing attention and made significant progress, particularly…
Non-confusing Generation of Customized Concepts in Diffusion Models
Wang Lin, Jingyuan Chen, Jiaxin Shi +8
We tackle the common challenge of inter-concept visual confusion in compositional concept generation using text-guided diffusion models (TGDMs). It becomes even more pronounced in…