30 citations · 44 across the 10 of their papers we have counts for
10 papers
Streaming Motion Forecasting for Autonomous Driving
Ziqi Pang, Deva Ramanan, Mengtian Li +1
Trajectory forecasting is a widely-studied problem for autonomous navigation. However, existing benchmarks evaluate forecasting based on independent snapshots of trajectories, whic…
Learning Lightweight Object Detectors via Multi-Teacher Progressive Distillation
Shengcao Cao, Mengtian Li, James Hays +3
Resource-constrained perception systems such as edge computing and vision-for-robotics require vision models to be both accurate and lightweight in computation and memory usage. Wh…
An Empirical Analysis of Range for 3D Object Detection
Neehar Peri, Mengtian Li, Benjamin Wilson +3
LiDAR-based 3D detection plays a vital role in autonomous navigation. Surprisingly, although autonomous vehicles (AVs) must detect both near-field objects (for collision avoidance)…
Far3Det: Towards Far-Field 3D Detection
Shubham Gupta, Jeet Kanjani, Mengtian Li +4
We focus on the task of far-field 3D detection (Far3Det) of objects beyond a certain distance from an observer, e.g., 50m. Far3Det is particularly important for autonomous vehic…
Forecasting from LiDAR via Future Object Detection
Neehar Peri, Jonathon Luiten, Mengtian Li +3
Object detection and forecasting are fundamental components of embodied perception. These two problems, however, are largely studied in isolation by the community. In this paper, w…
FOVEA: Foveated Image Magnification for Autonomous Navigation
Chittesh Thavamani, Mengtian Li, Nicolas Cebron +1
Efficient processing of high-res video streams is safety-critical for many robotics applications such as autonomous driving. To maintain real-time performance, many practical syste…
Towards Streaming Perception
Mengtian Li, Yu-Xiong Wang, Deva Ramanan
Embodied perception refers to the ability of an autonomous agent to perceive its environment so that it can (re)act. The responsiveness of the agent is largely governed by latency…
Budgeted Training: Rethinking Deep Neural Network Training Under Resource Constraints
Mengtian Li, Ersin Yumer, Deva Ramanan
In most practical settings and theoretical analyses, one assumes that a model can be trained until convergence. However, the growing complexity of machine learning datasets and mod…
Photo-Sketching: Inferring Contour Drawings from Images
Mengtian Li, Zhe Lin, Radomir Mech +2
Edges, boundaries and contours are important subjects of study in both computer graphics and computer vision. On one hand, they are the 2D elements that convey 3D shapes, on the ot…
Brute-Force Facial Landmark Analysis With A 140,000-Way Classifier
Mengtian Li, Laszlo Jeni, Deva Ramanan
We propose a simple approach to visual alignment, focusing on the illustrative task of facial landmark estimation. While most prior work treats this as a regression problem, we ins…