Search Results for author:
Found 17 papers, 8 papers with code
X-MIC: Cross-Modal Instance Conditioning for Egocentric Action Generalization
Lately, there has been growing interest in adapting vision-language models (VLMs) to image and third-person video classification due to their success in zero-shot recognition.
DiffH2O: Diffusion-Based Synthesis of Hand-Object Interactions from Textual Descriptions
In the grasping stage, the model only generates hand motions, whereas in the interaction phase both hand and object poses are synthesized.
On the Utility of 3D Hand Poses for Action Recognition
3D hand poses are an under-explored modality for action recognition.
Ranked #1 on
3D Action Recognition
on Assembly101
Opening the Vocabulary of Egocentric Actions
Given a set of verbs and objects observed during training, the goal is to generalize the verbs to an open vocabulary of actions with seen and novel objects.
Ranked #1 on
Open Vocabulary Action Recognition
on Assembly101
(using extra training data)
Every Mistake Counts in Assembly
Our framework constructs a knowledge base with spatial and temporal beliefs based on observed mistakes.
AssemblyHands: Towards Egocentric Activity Understanding via 3D Hand Pose Estimation
To obtain high-quality 3D hand pose annotations for the egocentric images, we develop an efficient pipeline, where we use an initial set of manual annotations to train a model to automatically annotate a much larger dataset.
Temporal Action Segmentation: An Analysis of Modern Techniques
Temporal action segmentation (TAS) in videos aims at densely identifying video frames in minutes-long videos with multiple action classes.
Assembly101: A Large-Scale Multi-View Video Dataset for Understanding Procedural Activities
Assembly101 is a new procedural activity dataset featuring 4321 videos of people assembling and disassembling 101 "take-apart" toy vehicles.
Transferring Knowledge from Text to Video: Zero-Shot Anticipation for Procedural Actions
Can we teach a robot to recognize and make predictions for activities that it has never seen before?
Transformed ROIs for Capturing Visual Transformations in Videos
Modeling the visual changes that an action brings to a scene is critical for video understanding.
Technical Report: Temporal Aggregate Representations
At what temporal scale should they be derived?
Ranked #5 on
Action Anticipation
on EPIC-KITCHENS-100 (test)
Temporal Aggregate Representations for Long-Range Video Understanding
Future prediction, especially in long-range videos, requires reasoning from current and past observations.
Ranked #2 on
Action Anticipation
on Assembly101
Unsupervised learning of action classes with continuous temporal embedding
The task of temporally detecting and segmenting actions in untrimmed videos has seen an increased attention recently.
Learning Style Compatibility for Furniture
When judging style, a key question that often arises is whether or not a pair of objects are compatible with each other.
Zero-Shot Anticipation for Instructional Activities
How can we teach a robot to predict what will happen next for an activity it has never seen before?
Unsupervised Learning and Segmentation of Complex Activities from Video
This paper presents a new method for unsupervised segmentation of complex activities from video into multiple steps, or sub-activities, without any textual input.
DRAW: Deep networks for Recognizing styles of Artists Who illustrate children's books
The style was noticeable in other characters of the same illustrator in different books as well.
