Publications

Detecting 3D objects from a single RGB image is intrinsically ambiguous, thus requiring appropriate prior knowledge and intermediate …

‘Thinking in pictures,’ [1] i.e., spatial-temporal reasoning, effortless and instantaneous for humans, is believed to be a …

We propose Bayesian Inverse Reinforcement Learning with Failure (BIRLF), which makes use of failed demonstrations that were often …

Transfer learning is fundamental for intelligence; agents expected to operate in novel and unfamiliar environments must be able to …

We propose VRGym, a virtual reality testbed for realistic human-robot interaction. Different from existing toolkits and virtual reality …

Dramatic progress has been witnessed in basic vision tasks involving low-level perception, such as object recognition, detection, and …

This paper presents an incremental learning framework for mobile robots localizing the human sound source using a microphone array in a …

This paper presents a design that jointly provides hand pose sensing, hand localization, and haptic feedback to facilitate real-time …

This paper presents a mirroring approach, inspired by the neuroscience discovery of the mirror neurons, to transfer demonstrated …

An unprecedented booming has been witnessed in the research area of artistic style transfer ever since Gatys et.al. introduced the …

Holistic 3D indoor scene understanding refers to jointly recovering the i) object bounding boxes, ii) room layout, and iii) camera …

We propose a computational framework to jointly parse a single RGB image and reconstruct a holistic 3D configuration composed by a set …

We propose a systematic learning-based approach to the generation of massive quantities of synthetic 3D scenes and arbitrary numbers of …

Discovery and application of causal knowledge in novel problem contexts is a prime example of human intelligence. As new information is …

We present a human-centric method to sample and synthesize 3D room layouts and 2D images thereof, for the purpose of obtaining …

Contact forces of the hand are visually unobservable, but play a crucial role in understanding hand-object interactions. In this paper, …

We present a novel Augmented Reality (AR) approach, through Microsoft HoloLens, to address the challenging problems of diagnosing, …

When a moving object collides with an object at rest, people immediately perceive a causal event: i.e., the first object has launched …

This paper studies a challenging problem of tracking severely occluded objects in long video sequences. The proposed method reasons …

Learning complex robot manipulation policies for real-world objects is challenging, often requiring significant tuning within …

We present a design of an easy-to-replicate glove-based system that can reliably perform simultaneous hand pose and force sensing in …

A growing body of evidence supports the hypothesis that humans infer future states of perceived physical situations by propagating …

This paper examines how humans adapt to novel physical situations with unknown gravitational acceleration in immersive virtual …

Both synthetic static and simulated dynamic 3D scene data is highly useful in the fields of computer vision and robot task planning. …

In this paper, we present a probabilistic approach to explicitly infer containment relations between objects in 3D scenes. Given an …

We propose a notion of affordance that takes into account physical quantities generated when the human body interacts with real-world …

The physical behavior of moving fluids is highly complex, yet people are able to interact with them in their everyday lives with …

In this paper, we present a new framework for task-oriented object modeling, learning and recognition. The framework include: i) …

Containers are ubiquitous in daily life. By container, we consider any physical object that can contain other objects, such as bowls, …

Google’s Android platform includes a permission model thatprotects access to sensitive capabilities, such as Internet ac-cess, …