Search Results for author: Dennis Park

Found 10 papers, 1 papers with code

Making Large Multimodal Models Understand Arbitrary Visual Prompts

no code implementations1 Dec 2023 Mu Cai, Haotian Liu, Siva Karthik Mustikovela, Gregory P. Meyer, Yuning Chai, Dennis Park, Yong Jae Lee

Furthermore, we present ViP-Bench, a comprehensive benchmark to assess the capability of models in understanding visual prompts across multiple dimensions, enabling future research in this domain.

Visual Commonsense Reasoning Visual Prompting

SHIFT3D: Synthesizing Hard Inputs For Tricking 3D Detectors

no code implementations ICCV 2023 Hongge Chen, Zhao Chen, Gregory P. Meyer, Dennis Park, Carl Vondrick, Ashish Shrivastava, Yuning Chai

We present SHIFT3D, a differentiable pipeline for generating 3D shapes that are structurally plausible yet challenging to 3D object detectors.

Autonomous Driving Object

What You Can Reconstruct From a Shadow

no code implementations CVPR 2023 Ruoshi Liu, Sachit Menon, Chengzhi Mao, Dennis Park, Simon Stent, Carl Vondrick

Experiments and visualizations show that the method is able to generate multiple possible solutions that are consistent with the observation of the shadow.

3D Reconstruction Object +1

Depth Is All You Need for Monocular 3D Detection

no code implementations5 Oct 2022 Dennis Park, Jie Li, Dian Chen, Vitor Guizilini, Adrien Gaidon

Our methods leverage commonly available LiDAR or RGB videos during training time to fine-tune the depth representation, which leads to improved 3D detectors.

Depth Prediction Monocular Depth Estimation +1

Shadows Shed Light on 3D Objects

no code implementations17 Jun 2022 Ruoshi Liu, Sachit Menon, Chengzhi Mao, Dennis Park, Simon Stent, Carl Vondrick

Experiments and visualizations show that the method is able to generate multiple possible solutions that are consistent with the observation of the shadow.

3D Reconstruction Object +1

Revealing Occlusions with 4D Neural Fields

no code implementations CVPR 2022 Basile Van Hoorick, Purva Tendulka, Didac Suris, Dennis Park, Simon Stent, Carl Vondrick

For computer vision systems to operate in dynamic situations, they need to be able to represent and reason about object permanence.

Video Understanding

Is Pseudo-Lidar needed for Monocular 3D Object detection?

2 code implementations ICCV 2021 Dennis Park, Rares Ambrus, Vitor Guizilini, Jie Li, Adrien Gaidon

Recent progress in 3D object detection from single images leverages monocular depth estimation as a way to produce 3D pointclouds, turning cameras into pseudo-lidar sensors.

 Ranked #1 on Monocular 3D Object Detection on KITTI Pedestrian Moderate (using extra training data)

Monocular 3D Object Detection Monocular Depth Estimation +2

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