5 citations · 12 across the 26 of their papers we have counts for
16 papers · 1 filter
DriveCritic: Towards Context-Aware, Human-Aligned Evaluation for Autonomous Driving with Vision-Language Models
Jingyu Song, Zhenxin Li, Shiyi Lan +6
Benchmarking autonomous driving planners to align with human judgment remains a critical challenge, as state-of-the-art metrics like the Extended Predictive Driver Model Score (EPD…
OmniDrive: A Holistic Vision-Language Dataset for Autonomous Driving with Counterfactual Reasoning
Shihao Wang, Zhiding Yu, Xiaohui Jiang +6
The advances in vision-language models (VLMs) have led to a growing interest in autonomous driving to leverage their strong reasoning capabilities. However, extending these capabil…
MDP: Multidimensional Vision Model Pruning with Latency Constraint
Xinglong Sun, Barath Lakshmanan, Maying Shen +3
Current structural pruning methods face two significant limitations: (i) they often limit pruning to finer-grained levels like channels, making aggressive parameter reduction chall…
Hydra-MDP++: Advancing End-to-End Driving via Expert-Guided Hydra-Distillation
Kailin Li, Zhenxin Li, Shiyi Lan +6
Hydra-MDP++ introduces a novel teacher-student knowledge distillation framework with a multi-head decoder that learns from human demonstrations and rule-based experts. Using a ligh…
Eagle 2: Building Post-Training Data Strategies from Scratch for Frontier Vision-Language Models
Zhiqi Li, Guo Chen, Shilong Liu +24
Recently, promising progress has been made by open-source vision-language models (VLMs) in bringing their capabilities closer to those of proprietary frontier models. However, most…
StreamChat: Chatting with Streaming Video
Jihao Liu, Zhiding Yu, Shiyi Lan +5
This paper presents StreamChat, a novel approach that enhances the interaction capabilities of Large Multimodal Models (LMMs) with streaming video content. In streaming interaction…
Exploring Camera Encoder Designs for Autonomous Driving Perception
Barath Lakshmanan, Joshua Chen, Shiyi Lan +3
The cornerstone of autonomous vehicles (AV) is a solid perception system, where camera encoders play a crucial role. Existing works usually leverage pre-trained Convolutional Neura…
Multi-Dimensional Pruning: Joint Channel, Layer and Block Pruning with Latency Constraint
Xinglong Sun, Barath Lakshmanan, Maying Shen +3
As we push the boundaries of performance in various vision tasks, the models grow in size correspondingly. To keep up with this growth, we need very aggressive pruning techniques f…
Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillation
Zhenxin Li, Kailin Li, Shihao Wang +9
We propose Hydra-MDP, a novel paradigm employing multiple teachers in a teacher-student model. This approach uses knowledge distillation from both human and rule-based teachers to…
OmniDrive: A Holistic Vision-Language Dataset for Autonomous Driving with Counterfactual Reasoning
Shihao Wang, Zhiding Yu, Xiaohui Jiang +6
The advances in vision-language models (VLMs) have led to a growing interest in autonomous driving to leverage their strong reasoning capabilities. However, extending these capabil…
What is Point Supervision Worth in Video Instance Segmentation?
Shuaiyi Huang, De-An Huang, Zhiding Yu +5
Video instance segmentation (VIS) is a challenging vision task that aims to detect, segment, and track objects in videos. Conventional VIS methods rely on densely-annotated object…
Fully Attentional Networks with Self-emerging Token Labeling
Bingyin Zhao, Zhiding Yu, Shiyi Lan +4
Recent studies indicate that Vision Transformers (ViTs) are robust against out-of-distribution scenarios. In particular, the Fully Attentional Network (FAN) - a family of ViT backb…
A Semantic Space is Worth 256 Language Descriptions: Make Stronger Segmentation Models with Descriptive Properties
Junfei Xiao, Ziqi Zhou, Wenxuan Li +6
This paper introduces ProLab, a novel approach using property-level label space for creating strong interpretable segmentation models. Instead of relying solely on category-specifi…
Is Ego Status All You Need for Open-Loop End-to-End Autonomous Driving?
Zhiqi Li, Zhiding Yu, Shiyi Lan +4
End-to-end autonomous driving recently emerged as a promising research direction to target autonomy from a full-stack perspective. Along this line, many of the latest works follow…
BEVNeXt: Reviving Dense BEV Frameworks for 3D Object Detection
Zhenxin Li, Shiyi Lan, Jose M. Alvarez +1
Recently, the rise of query-based Transformer decoders is reshaping camera-based 3D object detection. These query-based decoders are surpassing the traditional dense BEV (Bird's Ey…
Synthesize, Diagnose, and Optimize: Towards Fine-Grained Vision-Language Understanding
Wujian Peng, Sicheng Xie, Zuyao You +2
Vision language models (VLM) have demonstrated remarkable performance across various downstream tasks. However, understanding fine-grained visual-linguistic concepts, such as attri…