283 citations · 470 across the 84 of their papers we have counts for
13 papers · 1 filter
EgoPoints: Advancing Point Tracking for Egocentric Videos
Ahmad Darkhalil, Rhodri Guerrier, Adam W. Harley +1
We introduce EgoPoints, a benchmark for point tracking in egocentric videos. We annotate 4.7K challenging tracks in egocentric sequences. Compared to the popular TAP-Vid-DAVIS eval…
Scaling 4D Representations
João Carreira, Dilara Gokay, Michael King +32
Scaling has not yet been convincingly demonstrated for pure self-supervised learning from video. However, prior work has focused evaluations on semantic-related tasks $\unicode{x20…
ShowHowTo: Generating Scene-Conditioned Step-by-Step Visual Instructions
Tomáš Souček, Prajwal Gatti, Michael Wray +3
The goal of this work is to generate step-by-step visual instructions in the form of a sequence of images, given an input image that provides the scene context and the sequence of…
Perception Test 2024: Challenge Summary and a Novel Hour-Long VideoQA Benchmark
Joseph Heyward, João Carreira, Dima Damen +2
Following the successful 2023 edition, we organised the Second Perception Test challenge as a half-day workshop alongside the IEEE/CVF European Conference on Computer Vision (ECCV)…
Context-Aware Multimodal Pretraining
Karsten Roth, Zeynep Akata, Dima Damen +2
Large-scale multimodal representation learning successfully optimizes for zero-shot transfer at test time. Yet the standard pretraining paradigm (contrastive learning on large amou…
It's Just Another Day: Unique Video Captioning by Discriminative Prompting
Toby Perrett, Tengda Han, Dima Damen +1
Long videos contain many repeating actions, events and shots. These repetitions are frequently given identical captions, which makes it difficult to retrieve the exact desired clip…
AMEGO: Active Memory from long EGOcentric videos
Gabriele Goletto, Tushar Nagarajan, Giuseppe Averta +1
Egocentric videos provide a unique perspective into individuals' daily experiences, yet their unstructured nature presents challenges for perception. In this paper, we introduce AM…
Rank2Reward: Learning Shaped Reward Functions from Passive Video
Daniel Yang, Davin Tjia, Jacob Berg +3
Teaching robots novel skills with demonstrations via human-in-the-loop data collection techniques like kinesthetic teaching or teleoperation puts a heavy burden on human supervisor…
HOI-Ref: Hand-Object Interaction Referral in Egocentric Vision
Siddhant Bansal, Michael Wray, Dima Damen
Large Vision Language Models (VLMs) are now the de facto state-of-the-art for a number of tasks including visual question answering, recognising objects, and spatial referral. In t…
TIM: A Time Interval Machine for Audio-Visual Action Recognition
Jacob Chalk, Jaesung Huh, Evangelos Kazakos +2
Diverse actions give rise to rich audio-visual signals in long videos. Recent works showcase that the two modalities of audio and video exhibit different temporal extents of events…
Spatial Cognition from Egocentric Video: Out of Sight, Not Out of Mind
Chiara Plizzari, Shubham Goel, Toby Perrett +3
As humans move around, performing their daily tasks, they are able to recall where they have positioned objects in their environment, even if these objects are currently out of the…
Every Shot Counts: Using Exemplars for Repetition Counting in Videos
Saptarshi Sinha, Alexandros Stergiou, Dima Damen
Video repetition counting infers the number of repetitions of recurring actions or motion within a video. We propose an exemplar-based approach that discovers visual correspondence…
Video Editing for Video Retrieval
Bin Zhu, Kevin Flanagan, Adriano Fragomeni +2
Though pre-training vision-language models have demonstrated significant benefits in boosting video-text retrieval performance from large-scale web videos, fine-tuning still plays…