26 citations · 26 across the 12 of their papers we have counts for
13 papers · 1 filter
You Only Reprogram Once: Rethinking Prolonged Training for Visual Reprogramming
Zizhao Li, Mohammed Yaqoob Ansari, Xinyu Su +3
Visual reprogramming is a parameter-efficient method for adapting pretrained models, yet its training can remain computationally expensive: even with a frozen backbone, visual prom…
SceneForge: Structured World Supervision from 3D Interventions
Jizhizi Li, Jiayang Ao, Danny Wicks +1
Many multimodal learning tasks require supervision that remains consistent across edits, viewpoints, and scene-level interventions. However, such supervision is difficult to obtain…
Neural Distribution Prior for LiDAR Out-of-Distribution Detection
Zizhao Li, Zhengkang Xiang, Jiayang Ao +3
LiDAR-based perception is critical for autonomous driving due to its robustness to poor lighting and visibility conditions. Yet, current models operate under the closed-set assumpt…
Reasoning-Driven Amodal Completion: Collaborative Agents and Perceptual Evaluation
Hongxing Fan, Shuyu Zhao, Jiayang Ao +1
Amodal completion, the task of inferring invisible object parts, faces significant challenges in maintaining semantic consistency and structural integrity. Prior progressive approa…
PointNet4D: A Lightweight 4D Point Cloud Video Backbone for Online and Offline Perception in Robotic Applications
Yunze Liu, Zifan Wang, Peiran Wu +1
Understanding dynamic 4D environments-3D space evolving over time-is critical for robotic and interactive systems. These applications demand systems that can process streaming poin…
Relative Energy Learning for LiDAR Out-of-Distribution Detection
Zizhao Li, Zhengkang Xiang, Jiayang Ao +2
Out-of-distribution (OOD) detection is a critical requirement for reliable autonomous driving, where safety depends on recognizing road obstacles and unexpected objects beyond the…
FG-CLIP 2: A Bilingual Fine-grained Vision-Language Alignment Model
Chunyu Xie, Bin Wang, Fanjing Kong +5
Fine-grained vision-language understanding requires precise alignment between visual content and linguistic descriptions, a capability that remains limited in current models, parti…
LMM-Det: Make Large Multimodal Models Excel in Object Detection
Jincheng Li, Chunyu Xie, Ji Ao +2
Large multimodal models (LMMs) have garnered wide-spread attention and interest within the artificial intelligence research and industrial communities, owing to their remarkable ca…
Beyond Perception: Evaluating Abstract Visual Reasoning through Multi-Stage Task
Yanbei Jiang, Yihao Ding, Chao Lei +3
Current Multimodal Large Language Models (MLLMs) excel in general visual reasoning but remain underexplored in Abstract Visual Reasoning (AVR), which demands higher-order reasoning…
Open-World Amodal Appearance Completion
Jiayang Ao, Yanbei Jiang, Qiuhong Ke +1
Understanding and reconstructing occluded objects is a challenging problem, especially in open-world scenarios where categories and contexts are diverse and unpredictable. Traditio…
Sequential Amodal Segmentation via Cumulative Occlusion Learning
Jiayang Ao, Qiuhong Ke, Krista A. Ehinger
To fully understand the 3D context of a single image, a visual system must be able to segment both the visible and occluded regions of objects, while discerning their occlusion ord…
Amodal Intra-class Instance Segmentation: Synthetic Datasets and Benchmark
Jiayang Ao, Qiuhong Ke, Krista A. Ehinger
Images of realistic scenes often contain intra-class objects that are heavily occluded from each other, making the amodal perception task that requires parsing the occluded parts o…
Image Amodal Completion: A Survey
Jiayang Ao, Qiuhong Ke, Krista A. Ehinger
Existing computer vision systems can compete with humans in understanding the visible parts of objects, but still fall far short of humans when it comes to depicting the invisible…