21 citations · 28 across the 30 of their papers we have counts for
13 papers · 1 filter
Cut-ViT: Task-Specific Model Pruning via Gram Anchoring Subspace Consistency
Jianjian Yin, Liulei Li, Tao Chen +3
Pruning visual foundation models has attracted considerable attention. However, existing methods focus on rigid point-to-point token alignment on a single dataset for pruning, suff…
From Reasoning to Pixels: Grounded Medical Multimodal LLMs for VQA and Segmentation
Haowen Gu, Gensheng Pei, Junzhu Mao +3
Although Multimodal Large Language Models (MLLMs) have demonstrated impressive performance in Medical Visual Question Answering (Med-VQA), their reliance on global image features o…
MedFG-VQA: Low-Frequency Memory and Graph Attention for Lightweight Medical VQA
Haowen Gu, Gensheng Pei, Zeren Sun +4
Medical Visual Question Answering (Med-VQA) holds significant promise for clinical decision support, yet faces challenges due to limited annotated data and the high computational d…
Rethinking Point Clouds as Sequences: A Causal Next-Token Predictive Learning Framework
Yumeng Yao, Jingzhi Dong, Haowen Gu +4
With the rapid progress of multimodal foundation models and predictive pre-training, an important open question is how to equip 3D point clouds with a pre-training paradigm that is…
PEARL: Geometry Aligns Semantics for Training-Free Open-Vocabulary Semantic Segmentation
Gensheng Pei, Xiruo Jiang, Xinhao Cai +3
Training-free open-vocabulary semantic segmentation (OVSS) promises rapid adaptation to new label sets without retraining. Yet, many methods rely on heavy post-processing or handle…
Efficiency Follows Global-Local Decoupling
Zhenyu Yang, Gensheng Pei, Tao Chen +4
Modern vision models must capture image-level context without sacrificing local detail while remaining computationally affordable. We revisit this tradeoff and advance a simple pri…
Iris: Bringing Real-World Priors into Diffusion Model for Monocular Depth Estimation
Xinhao Cai, Gensheng Pei, Zeren Sun +3
In this paper, we propose \textbf{Iris}, a deterministic framework for Monocular Depth Estimation (MDE) that integrates real-world priors into the diffusion model. Conventional fee…
PCA-Seg: Revisiting Cost Aggregation for Open-Vocabulary Semantic and Part Segmentation
Jianjian Yin, Tao Chen, Yi Chen +4
Recent advances in vision-language models (VLMs) have garnered substantial attention in open-vocabulary semantic and part segmentation (OSPS). However, existing methods extract ima…
PKINet-v2: Towards Powerful and Efficient Poly-Kernel Remote Sensing Object Detection
Xinhao Cai, Liulei Li, Gensheng Pei +3
Object detection in remote sensing images (RSIs) is challenged by the coexistence of geometric and spatial complexity: targets may appear with diverse aspect ratios, while spanning…
Towards Remote Sensing Change Detection with Neural Memory
Zhenyu Yang, Gensheng Pei, Yazhou Yao +3
Remote sensing change detection is essential for environmental monitoring, urban planning, and related applications. However, current methods often struggle to capture long-range d…
Taming SAM3 in the Wild: A Concept Bank for Open-Vocabulary Segmentation
Gensheng Pei, Xiruo Jiang, Yazhou Yao +3
The recent introduction of \texttt{SAM3} has revolutionized Open-Vocabulary Segmentation (OVS) through \textit{promptable concept segmentation}, which grounds pixel predictions in…
Combating Noisy Labels through Fostering Self- and Neighbor-Consistency
Zeren Sun, Yazhou Yao, Tongliang Liu +3
Label noise is pervasive in various real-world scenarios, posing challenges in supervised deep learning. Deep networks are vulnerable to such label-corrupted samples due to the mem…
AbductiveMLLM: Boosting Visual Abductive Reasoning Within MLLMs
Boyu Chang, Qi Wang, Xi Guo +3
Visual abductive reasoning (VAR) is a challenging task that requires AI systems to infer the most likely explanation for incomplete visual observations. While recent MLLMs develop…